09/29/2023 23:17:38 - WARNING - __main__ -   Process rank: -1, device: cuda, n_gpu: 1, distributed training: False, 16-bits training: False
09/29/2023 23:17:49 - INFO - __main__ -   Training/evaluation parameters Namespace(train_file='../../../data/mcqa/atomic/train_atmc_2i_100k_name.jsonl', dev_file='../../../data/mcqa/atomic/dev_atmc_SyntheticQA_10k.jsonl', model_type='deberta-mlm', model_name_or_path='microsoft/deberta-v3-large', config_name='', tokenizer_name='', cache_dir='.cache', task_name='atomic', output_dir='output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', second_train_file=None, second_dev_file=None, max_seq_length=128, max_words_to_mask=6, max_sequence_per_time=80, do_train=True, do_eval=True, do_ext_eval=True, evaluate_during_training=True, do_lower_case=False, per_gpu_train_batch_size=2, per_gpu_eval_batch_size=32, gradient_accumulation_steps=16, margin=1.0, learning_rate=5e-06, weight_decay=0.01, adam_epsilon=1e-06, max_grad_norm=1.0, num_train_epochs=1.0, max_steps=-1, warmup_steps=0, warmup_proportion=0.05, logging_steps=50, save_steps=200, logits_file='logits_test.txt', results_file='eval_results.txt', no_cuda=False, overwrite_output_dir=False, seed=101, fp16=False, fp16_opt_level='O1', local_rank=-1, server_ip='', server_port='', eval_output_dir='./eval_results', n_gpu=1, device=device(type='cuda'))
09/29/2023 23:17:58 - INFO - __main__ -   ***** Running evaluation *****
09/29/2023 23:17:58 - INFO - __main__ -     Num examples = 10000
09/29/2023 23:17:58 - INFO - __main__ -     Batch size = 32
09/29/2023 23:22:13 - INFO - __main__ -   ***** Eval results *****
09/29/2023 23:22:13 - INFO - __main__ -     acc = 0.3356
09/29/2023 23:32:56 - INFO - __main__ -   warm up steps = 916
09/29/2023 23:32:56 - INFO - __main__ -   ***** Running training *****
09/29/2023 23:32:56 - INFO - __main__ -     Num examples = 586778
09/29/2023 23:32:56 - INFO - __main__ -     Num Epochs = 1
09/29/2023 23:32:56 - INFO - __main__ -     Instantaneous batch size per GPU = 2
09/29/2023 23:32:56 - INFO - __main__ -     Total train batch size (w. parallel, distributed & accumulation) = 32
09/29/2023 23:32:56 - INFO - __main__ -     Gradient Accumulation steps = 16
09/29/2023 23:32:56 - INFO - __main__ -     Total optimization steps = 18336
09/29/2023 23:36:55 - INFO - __main__ -    global_step = 50, average loss = 0.6978485188353807
09/29/2023 23:41:05 - INFO - __main__ -    global_step = 100, average loss = 0.6761001783981919
09/29/2023 23:45:18 - INFO - __main__ -    global_step = 150, average loss = 0.6527128890505992
09/29/2023 23:49:15 - INFO - __main__ -    global_step = 200, average loss = 0.6255776268531917
09/29/2023 23:49:16 - INFO - __main__ -   ***** Running evaluation *****
09/29/2023 23:49:16 - INFO - __main__ -     Num examples = 10000
09/29/2023 23:49:16 - INFO - __main__ -     Batch size = 32
09/29/2023 23:53:34 - INFO - __main__ -   ***** Eval results *****
09/29/2023 23:53:34 - INFO - __main__ -     acc = 0.3839
09/29/2023 23:54:05 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/29/2023 23:58:03 - INFO - __main__ -    global_step = 250, average loss = 0.5687153974524699
09/30/2023 00:02:07 - INFO - __main__ -    global_step = 300, average loss = 0.4650766727951122
09/30/2023 00:06:15 - INFO - __main__ -    global_step = 350, average loss = 0.344281620121983
09/30/2023 00:10:25 - INFO - __main__ -    global_step = 400, average loss = 0.2641717765412432
09/30/2023 00:10:26 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 00:10:26 - INFO - __main__ -     Num examples = 10000
09/30/2023 00:10:26 - INFO - __main__ -     Batch size = 32
09/30/2023 00:14:45 - INFO - __main__ -   ***** Eval results *****
09/30/2023 00:14:45 - INFO - __main__ -     acc = 0.6657
09/30/2023 00:15:14 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 00:19:09 - INFO - __main__ -    global_step = 450, average loss = 0.203622583138349
09/30/2023 00:23:15 - INFO - __main__ -    global_step = 500, average loss = 0.19167841194193896
09/30/2023 00:27:33 - INFO - __main__ -    global_step = 550, average loss = 0.1768511165331256
09/30/2023 00:31:46 - INFO - __main__ -    global_step = 600, average loss = 0.17364913663874176
09/30/2023 00:31:47 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 00:31:47 - INFO - __main__ -     Num examples = 10000
09/30/2023 00:31:47 - INFO - __main__ -     Batch size = 32
09/30/2023 00:36:06 - INFO - __main__ -   ***** Eval results *****
09/30/2023 00:36:06 - INFO - __main__ -     acc = 0.7383
09/30/2023 00:36:35 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 00:40:35 - INFO - __main__ -    global_step = 650, average loss = 0.16046627445422929
09/30/2023 00:44:50 - INFO - __main__ -    global_step = 700, average loss = 0.15604460480608395
09/30/2023 00:49:12 - INFO - __main__ -    global_step = 750, average loss = 0.16073274322843645
09/30/2023 00:53:44 - INFO - __main__ -    global_step = 800, average loss = 0.15695772335122457
09/30/2023 00:53:44 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 00:53:44 - INFO - __main__ -     Num examples = 10000
09/30/2023 00:53:44 - INFO - __main__ -     Batch size = 32
09/30/2023 00:58:03 - INFO - __main__ -   ***** Eval results *****
09/30/2023 00:58:03 - INFO - __main__ -     acc = 0.7684
09/30/2023 00:58:33 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 01:02:32 - INFO - __main__ -    global_step = 850, average loss = 0.14848782167286118
09/30/2023 01:06:57 - INFO - __main__ -    global_step = 900, average loss = 0.12806821554375347
09/30/2023 01:11:28 - INFO - __main__ -    global_step = 950, average loss = 0.1180885765995481
09/30/2023 01:15:52 - INFO - __main__ -    global_step = 1000, average loss = 0.13545685631077503
09/30/2023 01:15:53 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 01:15:53 - INFO - __main__ -     Num examples = 10000
09/30/2023 01:15:53 - INFO - __main__ -     Batch size = 32
09/30/2023 01:20:11 - INFO - __main__ -   ***** Eval results *****
09/30/2023 01:20:11 - INFO - __main__ -     acc = 0.7644
09/30/2023 01:24:17 - INFO - __main__ -    global_step = 1050, average loss = 0.11866092401789502
09/30/2023 01:28:20 - INFO - __main__ -    global_step = 1100, average loss = 0.12610675325471676
09/30/2023 01:32:47 - INFO - __main__ -    global_step = 1150, average loss = 0.10549746582400985
09/30/2023 01:37:16 - INFO - __main__ -    global_step = 1200, average loss = 0.12280375221620489
09/30/2023 01:37:17 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 01:37:17 - INFO - __main__ -     Num examples = 10000
09/30/2023 01:37:17 - INFO - __main__ -     Batch size = 32
09/30/2023 01:41:35 - INFO - __main__ -   ***** Eval results *****
09/30/2023 01:41:35 - INFO - __main__ -     acc = 0.7802
09/30/2023 01:42:04 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 01:46:00 - INFO - __main__ -    global_step = 1250, average loss = 0.11540970739923068
09/30/2023 01:50:18 - INFO - __main__ -    global_step = 1300, average loss = 0.1098322441923665
09/30/2023 01:54:50 - INFO - __main__ -    global_step = 1350, average loss = 0.12102181358681265
09/30/2023 01:59:20 - INFO - __main__ -    global_step = 1400, average loss = 0.11920341529325014
09/30/2023 01:59:20 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 01:59:20 - INFO - __main__ -     Num examples = 10000
09/30/2023 01:59:20 - INFO - __main__ -     Batch size = 32
09/30/2023 02:03:40 - INFO - __main__ -   ***** Eval results *****
09/30/2023 02:03:40 - INFO - __main__ -     acc = 0.7991
09/30/2023 02:04:09 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 02:08:14 - INFO - __main__ -    global_step = 1450, average loss = 0.12416476066496215
09/30/2023 02:12:18 - INFO - __main__ -    global_step = 1500, average loss = 0.11171700998882443
09/30/2023 02:16:39 - INFO - __main__ -    global_step = 1550, average loss = 0.11893717237122474
09/30/2023 02:21:18 - INFO - __main__ -    global_step = 1600, average loss = 0.11236542866332457
09/30/2023 02:21:18 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 02:21:18 - INFO - __main__ -     Num examples = 10000
09/30/2023 02:21:18 - INFO - __main__ -     Batch size = 32
09/30/2023 02:25:38 - INFO - __main__ -   ***** Eval results *****
09/30/2023 02:25:38 - INFO - __main__ -     acc = 0.7998
09/30/2023 02:26:08 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 02:30:17 - INFO - __main__ -    global_step = 1650, average loss = 0.11477049457775138
09/30/2023 02:34:26 - INFO - __main__ -    global_step = 1700, average loss = 0.10185962059051235
09/30/2023 02:38:45 - INFO - __main__ -    global_step = 1750, average loss = 0.08941184240770554
09/30/2023 02:43:11 - INFO - __main__ -    global_step = 1800, average loss = 0.12326178842118679
09/30/2023 02:43:11 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 02:43:11 - INFO - __main__ -     Num examples = 10000
09/30/2023 02:43:11 - INFO - __main__ -     Batch size = 32
09/30/2023 02:47:30 - INFO - __main__ -   ***** Eval results *****
09/30/2023 02:47:30 - INFO - __main__ -     acc = 0.7949
09/30/2023 02:51:33 - INFO - __main__ -    global_step = 1850, average loss = 0.1172889139153267
09/30/2023 02:55:34 - INFO - __main__ -    global_step = 1900, average loss = 0.11077741613984472
09/30/2023 02:59:53 - INFO - __main__ -    global_step = 1950, average loss = 0.11476122897045571
09/30/2023 03:04:26 - INFO - __main__ -    global_step = 2000, average loss = 0.11272342270149238
09/30/2023 03:04:27 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 03:04:27 - INFO - __main__ -     Num examples = 10000
09/30/2023 03:04:27 - INFO - __main__ -     Batch size = 32
09/30/2023 03:08:46 - INFO - __main__ -   ***** Eval results *****
09/30/2023 03:08:46 - INFO - __main__ -     acc = 0.796
09/30/2023 03:12:55 - INFO - __main__ -    global_step = 2050, average loss = 0.10859557473420864
09/30/2023 03:17:10 - INFO - __main__ -    global_step = 2100, average loss = 0.09719053598862956
09/30/2023 03:21:26 - INFO - __main__ -    global_step = 2150, average loss = 0.11492000469923369
09/30/2023 03:25:59 - INFO - __main__ -    global_step = 2200, average loss = 0.09694181648810626
09/30/2023 03:25:59 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 03:25:59 - INFO - __main__ -     Num examples = 10000
09/30/2023 03:25:59 - INFO - __main__ -     Batch size = 32
09/30/2023 03:30:18 - INFO - __main__ -   ***** Eval results *****
09/30/2023 03:30:18 - INFO - __main__ -     acc = 0.7974
09/30/2023 03:34:20 - INFO - __main__ -    global_step = 2250, average loss = 0.10450371610718548
09/30/2023 03:38:29 - INFO - __main__ -    global_step = 2300, average loss = 0.09968944377507796
09/30/2023 03:42:35 - INFO - __main__ -    global_step = 2350, average loss = 0.09726969640512834
09/30/2023 03:46:47 - INFO - __main__ -    global_step = 2400, average loss = 0.10790286644703884
09/30/2023 03:46:48 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 03:46:48 - INFO - __main__ -     Num examples = 10000
09/30/2023 03:46:48 - INFO - __main__ -     Batch size = 32
09/30/2023 03:51:06 - INFO - __main__ -   ***** Eval results *****
09/30/2023 03:51:06 - INFO - __main__ -     acc = 0.8019
09/30/2023 03:51:36 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 03:55:37 - INFO - __main__ -    global_step = 2450, average loss = 0.0904800341839109
09/30/2023 03:59:49 - INFO - __main__ -    global_step = 2500, average loss = 0.09749648973207513
09/30/2023 04:04:09 - INFO - __main__ -    global_step = 2550, average loss = 0.09015977876108082
09/30/2023 04:08:36 - INFO - __main__ -    global_step = 2600, average loss = 0.11385933604056846
09/30/2023 04:08:37 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 04:08:37 - INFO - __main__ -     Num examples = 10000
09/30/2023 04:08:37 - INFO - __main__ -     Batch size = 32
09/30/2023 04:12:54 - INFO - __main__ -   ***** Eval results *****
09/30/2023 04:12:54 - INFO - __main__ -     acc = 0.8079
09/30/2023 04:13:24 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 04:17:30 - INFO - __main__ -    global_step = 2650, average loss = 0.09506087936344557
09/30/2023 04:21:44 - INFO - __main__ -    global_step = 2700, average loss = 0.09819057766188052
09/30/2023 04:25:56 - INFO - __main__ -    global_step = 2750, average loss = 0.09318019706217456
09/30/2023 04:30:01 - INFO - __main__ -    global_step = 2800, average loss = 0.08744580631115241
09/30/2023 04:30:02 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 04:30:02 - INFO - __main__ -     Num examples = 10000
09/30/2023 04:30:02 - INFO - __main__ -     Batch size = 32
09/30/2023 04:34:20 - INFO - __main__ -   ***** Eval results *****
09/30/2023 04:34:20 - INFO - __main__ -     acc = 0.8088
09/30/2023 04:34:50 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 04:39:07 - INFO - __main__ -    global_step = 2850, average loss = 0.10302798340337177
09/30/2023 04:43:20 - INFO - __main__ -    global_step = 2900, average loss = 0.09180921425198903
09/30/2023 04:47:38 - INFO - __main__ -    global_step = 2950, average loss = 0.09286653973598731
09/30/2023 04:52:11 - INFO - __main__ -    global_step = 3000, average loss = 0.09590554324422555
09/30/2023 04:52:12 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 04:52:12 - INFO - __main__ -     Num examples = 10000
09/30/2023 04:52:12 - INFO - __main__ -     Batch size = 32
09/30/2023 04:56:30 - INFO - __main__ -   ***** Eval results *****
09/30/2023 04:56:30 - INFO - __main__ -     acc = 0.8082
09/30/2023 05:00:20 - INFO - __main__ -    global_step = 3050, average loss = 0.0994117746003758
09/30/2023 05:04:34 - INFO - __main__ -    global_step = 3100, average loss = 0.08591548198470264
09/30/2023 05:09:00 - INFO - __main__ -    global_step = 3150, average loss = 0.09913339292746969
09/30/2023 05:13:29 - INFO - __main__ -    global_step = 3200, average loss = 0.09553639550766092
09/30/2023 05:13:29 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 05:13:29 - INFO - __main__ -     Num examples = 10000
09/30/2023 05:13:29 - INFO - __main__ -     Batch size = 32
09/30/2023 05:17:46 - INFO - __main__ -   ***** Eval results *****
09/30/2023 05:17:46 - INFO - __main__ -     acc = 0.8013
09/30/2023 05:21:55 - INFO - __main__ -    global_step = 3250, average loss = 0.0932181820196638
09/30/2023 05:25:59 - INFO - __main__ -    global_step = 3300, average loss = 0.08498929560689703
09/30/2023 05:30:21 - INFO - __main__ -    global_step = 3350, average loss = 0.10022641647228739
09/30/2023 05:34:47 - INFO - __main__ -    global_step = 3400, average loss = 0.08711659569285984
09/30/2023 05:34:47 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 05:34:47 - INFO - __main__ -     Num examples = 10000
09/30/2023 05:34:47 - INFO - __main__ -     Batch size = 32
09/30/2023 05:39:06 - INFO - __main__ -   ***** Eval results *****
09/30/2023 05:39:06 - INFO - __main__ -     acc = 0.8085
09/30/2023 05:43:04 - INFO - __main__ -    global_step = 3450, average loss = 0.08860307957234909
09/30/2023 05:47:15 - INFO - __main__ -    global_step = 3500, average loss = 0.09122671313540195
09/30/2023 05:51:40 - INFO - __main__ -    global_step = 3550, average loss = 0.09726192618174537
09/30/2023 05:56:06 - INFO - __main__ -    global_step = 3600, average loss = 0.09295479882246582
09/30/2023 05:56:07 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 05:56:07 - INFO - __main__ -     Num examples = 10000
09/30/2023 05:56:07 - INFO - __main__ -     Batch size = 32
09/30/2023 06:00:25 - INFO - __main__ -   ***** Eval results *****
09/30/2023 06:00:25 - INFO - __main__ -     acc = 0.7981
09/30/2023 06:04:25 - INFO - __main__ -    global_step = 3650, average loss = 0.0850781474460382
09/30/2023 06:08:29 - INFO - __main__ -    global_step = 3700, average loss = 0.08510007355012932
09/30/2023 06:12:45 - INFO - __main__ -    global_step = 3750, average loss = 0.09091129492127947
09/30/2023 06:17:00 - INFO - __main__ -    global_step = 3800, average loss = 0.08938177831689245
09/30/2023 06:17:01 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 06:17:01 - INFO - __main__ -     Num examples = 10000
09/30/2023 06:17:01 - INFO - __main__ -     Batch size = 32
09/30/2023 06:21:19 - INFO - __main__ -   ***** Eval results *****
09/30/2023 06:21:19 - INFO - __main__ -     acc = 0.8008
09/30/2023 06:25:31 - INFO - __main__ -    global_step = 3850, average loss = 0.09504610720792699
09/30/2023 06:29:46 - INFO - __main__ -    global_step = 3900, average loss = 0.0801623915314849
09/30/2023 06:34:06 - INFO - __main__ -    global_step = 3950, average loss = 0.08579662030970212
09/30/2023 06:38:28 - INFO - __main__ -    global_step = 4000, average loss = 0.09399219373066443
09/30/2023 06:38:29 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 06:38:29 - INFO - __main__ -     Num examples = 10000
09/30/2023 06:38:29 - INFO - __main__ -     Batch size = 32
09/30/2023 06:42:47 - INFO - __main__ -   ***** Eval results *****
09/30/2023 06:42:47 - INFO - __main__ -     acc = 0.8075
09/30/2023 06:46:50 - INFO - __main__ -    global_step = 4050, average loss = 0.07777188256899535
09/30/2023 06:51:06 - INFO - __main__ -    global_step = 4100, average loss = 0.09610467369071557
09/30/2023 06:55:28 - INFO - __main__ -    global_step = 4150, average loss = 0.08811031442368403
09/30/2023 07:00:00 - INFO - __main__ -    global_step = 4200, average loss = 0.08664546085885377
09/30/2023 07:00:01 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 07:00:01 - INFO - __main__ -     Num examples = 10000
09/30/2023 07:00:01 - INFO - __main__ -     Batch size = 32
09/30/2023 07:04:19 - INFO - __main__ -   ***** Eval results *****
09/30/2023 07:04:19 - INFO - __main__ -     acc = 0.8193
09/30/2023 07:04:50 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 07:09:00 - INFO - __main__ -    global_step = 4250, average loss = 0.0982984783052234
09/30/2023 07:13:25 - INFO - __main__ -    global_step = 4300, average loss = 0.08057821323724056
09/30/2023 07:17:51 - INFO - __main__ -    global_step = 4350, average loss = 0.08660443297441817
09/30/2023 07:22:18 - INFO - __main__ -    global_step = 4400, average loss = 0.09301655420538736
09/30/2023 07:22:19 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 07:22:19 - INFO - __main__ -     Num examples = 10000
09/30/2023 07:22:19 - INFO - __main__ -     Batch size = 32
09/30/2023 07:26:36 - INFO - __main__ -   ***** Eval results *****
09/30/2023 07:26:36 - INFO - __main__ -     acc = 0.8113
09/30/2023 07:30:33 - INFO - __main__ -    global_step = 4450, average loss = 0.08599573986270116
09/30/2023 07:34:39 - INFO - __main__ -    global_step = 4500, average loss = 0.08530666312639369
09/30/2023 07:38:48 - INFO - __main__ -    global_step = 4550, average loss = 0.0846066818782856
09/30/2023 07:43:20 - INFO - __main__ -    global_step = 4600, average loss = 0.0817996960383789
09/30/2023 07:43:21 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 07:43:21 - INFO - __main__ -     Num examples = 10000
09/30/2023 07:43:21 - INFO - __main__ -     Batch size = 32
09/30/2023 07:47:39 - INFO - __main__ -   ***** Eval results *****
09/30/2023 07:47:39 - INFO - __main__ -     acc = 0.82
09/30/2023 07:48:09 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 07:52:15 - INFO - __main__ -    global_step = 4650, average loss = 0.09457363621040712
09/30/2023 07:56:34 - INFO - __main__ -    global_step = 4700, average loss = 0.09125612366977293
09/30/2023 08:01:01 - INFO - __main__ -    global_step = 4750, average loss = 0.08600258652179037
09/30/2023 08:05:26 - INFO - __main__ -    global_step = 4800, average loss = 0.09128527461645718
09/30/2023 08:05:26 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 08:05:26 - INFO - __main__ -     Num examples = 10000
09/30/2023 08:05:26 - INFO - __main__ -     Batch size = 32
09/30/2023 08:09:45 - INFO - __main__ -   ***** Eval results *****
09/30/2023 08:09:45 - INFO - __main__ -     acc = 0.8151
09/30/2023 08:13:38 - INFO - __main__ -    global_step = 4850, average loss = 0.09068508470605594
09/30/2023 08:17:36 - INFO - __main__ -    global_step = 4900, average loss = 0.08361487613161443
09/30/2023 08:21:45 - INFO - __main__ -    global_step = 4950, average loss = 0.09231334731652169
09/30/2023 08:26:13 - INFO - __main__ -    global_step = 5000, average loss = 0.09210781741610845
09/30/2023 08:26:13 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 08:26:13 - INFO - __main__ -     Num examples = 10000
09/30/2023 08:26:13 - INFO - __main__ -     Batch size = 32
09/30/2023 08:30:31 - INFO - __main__ -   ***** Eval results *****
09/30/2023 08:30:31 - INFO - __main__ -     acc = 0.8182
09/30/2023 08:34:31 - INFO - __main__ -    global_step = 5050, average loss = 0.0987089884125453
09/30/2023 08:38:41 - INFO - __main__ -    global_step = 5100, average loss = 0.08649987229902763
09/30/2023 08:43:07 - INFO - __main__ -    global_step = 5150, average loss = 0.08150071838943404
09/30/2023 08:47:36 - INFO - __main__ -    global_step = 5200, average loss = 0.09248840492458839
09/30/2023 08:47:36 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 08:47:36 - INFO - __main__ -     Num examples = 10000
09/30/2023 08:47:36 - INFO - __main__ -     Batch size = 32
09/30/2023 08:51:54 - INFO - __main__ -   ***** Eval results *****
09/30/2023 08:51:54 - INFO - __main__ -     acc = 0.8098
09/30/2023 08:56:07 - INFO - __main__ -    global_step = 5250, average loss = 0.08664297451652601
09/30/2023 09:00:14 - INFO - __main__ -    global_step = 5300, average loss = 0.0810040804851451
09/30/2023 09:04:19 - INFO - __main__ -    global_step = 5350, average loss = 0.08586231906258035
09/30/2023 09:08:41 - INFO - __main__ -    global_step = 5400, average loss = 0.06912091931983014
09/30/2023 09:08:41 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 09:08:41 - INFO - __main__ -     Num examples = 10000
09/30/2023 09:08:41 - INFO - __main__ -     Batch size = 32
09/30/2023 09:12:59 - INFO - __main__ -   ***** Eval results *****
09/30/2023 09:12:59 - INFO - __main__ -     acc = 0.8138
09/30/2023 09:17:04 - INFO - __main__ -    global_step = 5450, average loss = 0.08094093154666553
09/30/2023 09:21:20 - INFO - __main__ -    global_step = 5500, average loss = 0.08313021952490089
09/30/2023 09:25:34 - INFO - __main__ -    global_step = 5550, average loss = 0.08020198410889862
09/30/2023 09:30:01 - INFO - __main__ -    global_step = 5600, average loss = 0.08213623003844987
09/30/2023 09:30:01 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 09:30:01 - INFO - __main__ -     Num examples = 10000
09/30/2023 09:30:01 - INFO - __main__ -     Batch size = 32
09/30/2023 09:34:19 - INFO - __main__ -   ***** Eval results *****
09/30/2023 09:34:19 - INFO - __main__ -     acc = 0.8138
09/30/2023 09:38:25 - INFO - __main__ -    global_step = 5650, average loss = 0.0817357241499849
09/30/2023 09:42:30 - INFO - __main__ -    global_step = 5700, average loss = 0.07617272696845248
09/30/2023 09:46:47 - INFO - __main__ -    global_step = 5750, average loss = 0.08003306837461423
09/30/2023 09:51:07 - INFO - __main__ -    global_step = 5800, average loss = 0.08461861441275687
09/30/2023 09:51:07 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 09:51:07 - INFO - __main__ -     Num examples = 10000
09/30/2023 09:51:07 - INFO - __main__ -     Batch size = 32
09/30/2023 09:55:24 - INFO - __main__ -   ***** Eval results *****
09/30/2023 09:55:24 - INFO - __main__ -     acc = 0.819
09/30/2023 09:59:31 - INFO - __main__ -    global_step = 5850, average loss = 0.0827079386992773
09/30/2023 10:03:45 - INFO - __main__ -    global_step = 5900, average loss = 0.09033509934786707
09/30/2023 10:08:04 - INFO - __main__ -    global_step = 5950, average loss = 0.08679367909935536
09/30/2023 10:12:29 - INFO - __main__ -    global_step = 6000, average loss = 0.0677787430045646
09/30/2023 10:12:30 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 10:12:30 - INFO - __main__ -     Num examples = 10000
09/30/2023 10:12:30 - INFO - __main__ -     Batch size = 32
09/30/2023 10:16:48 - INFO - __main__ -   ***** Eval results *****
09/30/2023 10:16:48 - INFO - __main__ -     acc = 0.793
09/30/2023 10:20:46 - INFO - __main__ -    global_step = 6050, average loss = 0.07449474892706348
09/30/2023 10:24:57 - INFO - __main__ -    global_step = 6100, average loss = 0.08253852118214126
09/30/2023 10:29:21 - INFO - __main__ -    global_step = 6150, average loss = 0.07779288738580363
09/30/2023 10:33:50 - INFO - __main__ -    global_step = 6200, average loss = 0.08415637877900735
09/30/2023 10:33:51 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 10:33:51 - INFO - __main__ -     Num examples = 10000
09/30/2023 10:33:51 - INFO - __main__ -     Batch size = 32
09/30/2023 10:38:09 - INFO - __main__ -   ***** Eval results *****
09/30/2023 10:38:09 - INFO - __main__ -     acc = 0.8152
09/30/2023 10:42:10 - INFO - __main__ -    global_step = 6250, average loss = 0.0836084969737567
09/30/2023 10:46:22 - INFO - __main__ -    global_step = 6300, average loss = 0.09385589220066322
09/30/2023 10:50:35 - INFO - __main__ -    global_step = 6350, average loss = 0.09158665712571747
09/30/2023 10:55:02 - INFO - __main__ -    global_step = 6400, average loss = 0.0775194574438865
09/30/2023 10:55:03 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 10:55:03 - INFO - __main__ -     Num examples = 10000
09/30/2023 10:55:03 - INFO - __main__ -     Batch size = 32
09/30/2023 10:59:20 - INFO - __main__ -   ***** Eval results *****
09/30/2023 10:59:20 - INFO - __main__ -     acc = 0.8155
09/30/2023 11:03:28 - INFO - __main__ -    global_step = 6450, average loss = 0.08119687895305105
09/30/2023 11:07:51 - INFO - __main__ -    global_step = 6500, average loss = 0.07420433169674652
09/30/2023 11:12:28 - INFO - __main__ -    global_step = 6550, average loss = 0.06907126017362315
09/30/2023 11:16:58 - INFO - __main__ -    global_step = 6600, average loss = 0.07694708627823274
09/30/2023 11:16:58 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 11:16:58 - INFO - __main__ -     Num examples = 10000
09/30/2023 11:16:58 - INFO - __main__ -     Batch size = 32
09/30/2023 11:21:17 - INFO - __main__ -   ***** Eval results *****
09/30/2023 11:21:17 - INFO - __main__ -     acc = 0.8118
09/30/2023 11:25:39 - INFO - __main__ -    global_step = 6650, average loss = 0.07814562884639599
09/30/2023 11:30:08 - INFO - __main__ -    global_step = 6700, average loss = 0.08736841517616994
09/30/2023 11:34:35 - INFO - __main__ -    global_step = 6750, average loss = 0.08082478447904577
09/30/2023 11:39:03 - INFO - __main__ -    global_step = 6800, average loss = 0.07488631383661414
09/30/2023 11:39:04 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 11:39:04 - INFO - __main__ -     Num examples = 10000
09/30/2023 11:39:04 - INFO - __main__ -     Batch size = 32
09/30/2023 11:43:23 - INFO - __main__ -   ***** Eval results *****
09/30/2023 11:43:23 - INFO - __main__ -     acc = 0.8213
09/30/2023 11:43:49 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 11:47:44 - INFO - __main__ -    global_step = 6850, average loss = 0.08088931010104716
09/30/2023 11:51:57 - INFO - __main__ -    global_step = 6900, average loss = 0.07495710194933053
09/30/2023 11:56:20 - INFO - __main__ -    global_step = 6950, average loss = 0.08142732598964358
09/30/2023 12:00:40 - INFO - __main__ -    global_step = 7000, average loss = 0.08055740728428645
09/30/2023 12:00:41 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 12:00:41 - INFO - __main__ -     Num examples = 10000
09/30/2023 12:00:41 - INFO - __main__ -     Batch size = 32
09/30/2023 12:04:58 - INFO - __main__ -   ***** Eval results *****
09/30/2023 12:04:58 - INFO - __main__ -     acc = 0.8081
09/30/2023 12:08:49 - INFO - __main__ -    global_step = 7050, average loss = 0.08094024127516604
09/30/2023 12:13:05 - INFO - __main__ -    global_step = 7100, average loss = 0.08965814252063865
09/30/2023 12:17:22 - INFO - __main__ -    global_step = 7150, average loss = 0.07722920090716798
09/30/2023 12:21:45 - INFO - __main__ -    global_step = 7200, average loss = 0.08899519631431758
09/30/2023 12:21:46 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 12:21:46 - INFO - __main__ -     Num examples = 10000
09/30/2023 12:21:46 - INFO - __main__ -     Batch size = 32
09/30/2023 12:26:05 - INFO - __main__ -   ***** Eval results *****
09/30/2023 12:26:05 - INFO - __main__ -     acc = 0.8124
09/30/2023 12:30:21 - INFO - __main__ -    global_step = 7250, average loss = 0.06652378371007217
09/30/2023 12:34:39 - INFO - __main__ -    global_step = 7300, average loss = 0.07190304783754982
09/30/2023 12:39:04 - INFO - __main__ -    global_step = 7350, average loss = 0.07759228288079612
09/30/2023 12:43:26 - INFO - __main__ -    global_step = 7400, average loss = 0.07959542326259907
09/30/2023 12:43:27 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 12:43:27 - INFO - __main__ -     Num examples = 10000
09/30/2023 12:43:27 - INFO - __main__ -     Batch size = 32
09/30/2023 12:47:45 - INFO - __main__ -   ***** Eval results *****
09/30/2023 12:47:45 - INFO - __main__ -     acc = 0.8246
09/30/2023 12:48:12 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 12:52:13 - INFO - __main__ -    global_step = 7450, average loss = 0.07954016777908691
09/30/2023 12:56:27 - INFO - __main__ -    global_step = 7500, average loss = 0.06745836471483926
09/30/2023 13:00:43 - INFO - __main__ -    global_step = 7550, average loss = 0.07651237843449053
09/30/2023 13:04:59 - INFO - __main__ -    global_step = 7600, average loss = 0.08067735946224275
09/30/2023 13:05:00 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 13:05:00 - INFO - __main__ -     Num examples = 10000
09/30/2023 13:05:00 - INFO - __main__ -     Batch size = 32
09/30/2023 13:09:19 - INFO - __main__ -   ***** Eval results *****
09/30/2023 13:09:19 - INFO - __main__ -     acc = 0.8296
09/30/2023 13:09:45 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 13:13:52 - INFO - __main__ -    global_step = 7650, average loss = 0.07473264377593296
09/30/2023 13:18:02 - INFO - __main__ -    global_step = 7700, average loss = 0.07815635729657515
09/30/2023 13:22:14 - INFO - __main__ -    global_step = 7750, average loss = 0.08072268578209332
09/30/2023 13:26:29 - INFO - __main__ -    global_step = 7800, average loss = 0.0779763015091885
09/30/2023 13:26:30 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 13:26:30 - INFO - __main__ -     Num examples = 10000
09/30/2023 13:26:30 - INFO - __main__ -     Batch size = 32
09/30/2023 13:30:49 - INFO - __main__ -   ***** Eval results *****
09/30/2023 13:30:49 - INFO - __main__ -     acc = 0.8052
09/30/2023 13:34:56 - INFO - __main__ -    global_step = 7850, average loss = 0.08846644978621043
09/30/2023 13:39:08 - INFO - __main__ -    global_step = 7900, average loss = 0.08965322268464661
09/30/2023 13:43:18 - INFO - __main__ -    global_step = 7950, average loss = 0.07646228883138974
09/30/2023 13:47:34 - INFO - __main__ -    global_step = 8000, average loss = 0.06746727024801658
09/30/2023 13:47:35 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 13:47:35 - INFO - __main__ -     Num examples = 10000
09/30/2023 13:47:35 - INFO - __main__ -     Batch size = 32
09/30/2023 13:51:54 - INFO - __main__ -   ***** Eval results *****
09/30/2023 13:51:54 - INFO - __main__ -     acc = 0.8243
09/30/2023 13:56:06 - INFO - __main__ -    global_step = 8050, average loss = 0.08350399916278547
09/30/2023 14:00:19 - INFO - __main__ -    global_step = 8100, average loss = 0.06798540580417466
09/30/2023 14:04:46 - INFO - __main__ -    global_step = 8150, average loss = 0.06554304141827742
09/30/2023 14:09:04 - INFO - __main__ -    global_step = 8200, average loss = 0.06514280185193229
09/30/2023 14:09:05 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 14:09:05 - INFO - __main__ -     Num examples = 10000
09/30/2023 14:09:05 - INFO - __main__ -     Batch size = 32
09/30/2023 14:13:23 - INFO - __main__ -   ***** Eval results *****
09/30/2023 14:13:23 - INFO - __main__ -     acc = 0.8146
09/30/2023 14:17:36 - INFO - __main__ -    global_step = 8250, average loss = 0.07990871949750726
09/30/2023 14:21:47 - INFO - __main__ -    global_step = 8300, average loss = 0.07364155332470546
09/30/2023 14:25:52 - INFO - __main__ -    global_step = 8350, average loss = 0.08377082656683342
09/30/2023 14:30:12 - INFO - __main__ -    global_step = 8400, average loss = 0.07954915106311092
09/30/2023 14:30:13 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 14:30:13 - INFO - __main__ -     Num examples = 10000
09/30/2023 14:30:13 - INFO - __main__ -     Batch size = 32
09/30/2023 14:34:32 - INFO - __main__ -   ***** Eval results *****
09/30/2023 14:34:32 - INFO - __main__ -     acc = 0.8148
09/30/2023 14:38:42 - INFO - __main__ -    global_step = 8450, average loss = 0.07030039706209208
09/30/2023 14:42:55 - INFO - __main__ -    global_step = 8500, average loss = 0.08003189989045495
09/30/2023 14:47:10 - INFO - __main__ -    global_step = 8550, average loss = 0.07293609037540591
09/30/2023 14:51:25 - INFO - __main__ -    global_step = 8600, average loss = 0.07146468496641319
09/30/2023 14:51:25 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 14:51:25 - INFO - __main__ -     Num examples = 10000
09/30/2023 14:51:25 - INFO - __main__ -     Batch size = 32
09/30/2023 14:55:43 - INFO - __main__ -   ***** Eval results *****
09/30/2023 14:55:43 - INFO - __main__ -     acc = 0.8119
09/30/2023 14:59:48 - INFO - __main__ -    global_step = 8650, average loss = 0.08003535972715327
09/30/2023 15:03:55 - INFO - __main__ -    global_step = 8700, average loss = 0.06597046624192444
09/30/2023 15:08:18 - INFO - __main__ -    global_step = 8750, average loss = 0.07181154116915422
09/30/2023 15:12:39 - INFO - __main__ -    global_step = 8800, average loss = 0.068559150480869
09/30/2023 15:12:40 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 15:12:40 - INFO - __main__ -     Num examples = 10000
09/30/2023 15:12:40 - INFO - __main__ -     Batch size = 32
09/30/2023 15:16:57 - INFO - __main__ -   ***** Eval results *****
09/30/2023 15:16:57 - INFO - __main__ -     acc = 0.8027
09/30/2023 15:20:57 - INFO - __main__ -    global_step = 8850, average loss = 0.08192624930914462
09/30/2023 15:25:08 - INFO - __main__ -    global_step = 8900, average loss = 0.06891920362562814
09/30/2023 15:29:21 - INFO - __main__ -    global_step = 8950, average loss = 0.07183136703236868
09/30/2023 15:33:32 - INFO - __main__ -    global_step = 9000, average loss = 0.07862215217377524
09/30/2023 15:33:32 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 15:33:32 - INFO - __main__ -     Num examples = 10000
09/30/2023 15:33:32 - INFO - __main__ -     Batch size = 32
09/30/2023 15:37:51 - INFO - __main__ -   ***** Eval results *****
09/30/2023 15:37:51 - INFO - __main__ -     acc = 0.8145
09/30/2023 15:42:00 - INFO - __main__ -    global_step = 9050, average loss = 0.08039317954942816
09/30/2023 15:46:04 - INFO - __main__ -    global_step = 9100, average loss = 0.07681855217753991
09/30/2023 15:50:19 - INFO - __main__ -    global_step = 9150, average loss = 0.06908466021588539
09/30/2023 15:54:39 - INFO - __main__ -    global_step = 9200, average loss = 0.07285123934067088
09/30/2023 15:54:40 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 15:54:40 - INFO - __main__ -     Num examples = 10000
09/30/2023 15:54:40 - INFO - __main__ -     Batch size = 32
09/30/2023 15:58:58 - INFO - __main__ -   ***** Eval results *****
09/30/2023 15:58:58 - INFO - __main__ -     acc = 0.8157
09/30/2023 16:03:12 - INFO - __main__ -    global_step = 9250, average loss = 0.07457796319955377
09/30/2023 16:07:29 - INFO - __main__ -    global_step = 9300, average loss = 0.08509899367534672
09/30/2023 16:11:53 - INFO - __main__ -    global_step = 9350, average loss = 0.07013603730166323
09/30/2023 16:16:21 - INFO - __main__ -    global_step = 9400, average loss = 0.07017059165984392
09/30/2023 16:16:22 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 16:16:22 - INFO - __main__ -     Num examples = 10000
09/30/2023 16:16:22 - INFO - __main__ -     Batch size = 32
09/30/2023 16:20:40 - INFO - __main__ -   ***** Eval results *****
09/30/2023 16:20:40 - INFO - __main__ -     acc = 0.8141
09/30/2023 16:24:51 - INFO - __main__ -    global_step = 9450, average loss = 0.0831688746976215
09/30/2023 16:29:17 - INFO - __main__ -    global_step = 9500, average loss = 0.08576202854252188
09/30/2023 16:33:37 - INFO - __main__ -    global_step = 9550, average loss = 0.08213058317254764
09/30/2023 16:37:58 - INFO - __main__ -    global_step = 9600, average loss = 0.072965028858016
09/30/2023 16:37:58 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 16:37:58 - INFO - __main__ -     Num examples = 10000
09/30/2023 16:37:58 - INFO - __main__ -     Batch size = 32
09/30/2023 16:42:15 - INFO - __main__ -   ***** Eval results *****
09/30/2023 16:42:15 - INFO - __main__ -     acc = 0.8122
09/30/2023 16:46:15 - INFO - __main__ -    global_step = 9650, average loss = 0.07125714480011083
09/30/2023 16:50:19 - INFO - __main__ -    global_step = 9700, average loss = 0.07434062254025775
09/30/2023 16:54:30 - INFO - __main__ -    global_step = 9750, average loss = 0.07218598224179004
09/30/2023 16:58:52 - INFO - __main__ -    global_step = 9800, average loss = 0.06753908861952368
09/30/2023 16:58:52 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 16:58:52 - INFO - __main__ -     Num examples = 10000
09/30/2023 16:58:52 - INFO - __main__ -     Batch size = 32
09/30/2023 17:03:10 - INFO - __main__ -   ***** Eval results *****
09/30/2023 17:03:10 - INFO - __main__ -     acc = 0.8208
09/30/2023 17:07:12 - INFO - __main__ -    global_step = 9850, average loss = 0.0787789156648796
09/30/2023 17:11:24 - INFO - __main__ -    global_step = 9900, average loss = 0.06863431145990034
09/30/2023 17:15:44 - INFO - __main__ -    global_step = 9950, average loss = 0.0729100130192819
09/30/2023 17:20:01 - INFO - __main__ -    global_step = 10000, average loss = 0.07118722895695101
09/30/2023 17:20:01 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 17:20:01 - INFO - __main__ -     Num examples = 10000
09/30/2023 17:20:01 - INFO - __main__ -     Batch size = 32
09/30/2023 17:24:20 - INFO - __main__ -   ***** Eval results *****
09/30/2023 17:24:20 - INFO - __main__ -     acc = 0.8212
09/30/2023 17:28:25 - INFO - __main__ -    global_step = 10050, average loss = 0.06967489041242515
09/30/2023 17:32:40 - INFO - __main__ -    global_step = 10100, average loss = 0.07503812584323896
09/30/2023 17:37:07 - INFO - __main__ -    global_step = 10150, average loss = 0.07984486830362585
09/30/2023 17:41:19 - INFO - __main__ -    global_step = 10200, average loss = 0.06886661994401948
09/30/2023 17:41:19 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 17:41:19 - INFO - __main__ -     Num examples = 10000
09/30/2023 17:41:19 - INFO - __main__ -     Batch size = 32
09/30/2023 17:45:37 - INFO - __main__ -   ***** Eval results *****
09/30/2023 17:45:37 - INFO - __main__ -     acc = 0.8134
09/30/2023 17:49:55 - INFO - __main__ -    global_step = 10250, average loss = 0.07405807184350124
09/30/2023 17:54:14 - INFO - __main__ -    global_step = 10300, average loss = 0.08030594819738326
09/30/2023 17:58:33 - INFO - __main__ -    global_step = 10350, average loss = 0.08568550381663954
09/30/2023 18:02:39 - INFO - __main__ -    global_step = 10400, average loss = 0.08110691699486779
09/30/2023 18:02:39 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 18:02:39 - INFO - __main__ -     Num examples = 10000
09/30/2023 18:02:39 - INFO - __main__ -     Batch size = 32
09/30/2023 18:07:00 - INFO - __main__ -   ***** Eval results *****
09/30/2023 18:07:00 - INFO - __main__ -     acc = 0.8226
09/30/2023 18:10:59 - INFO - __main__ -    global_step = 10450, average loss = 0.07698049577564234
09/30/2023 18:15:18 - INFO - __main__ -    global_step = 10500, average loss = 0.07489776252514276
09/30/2023 18:19:38 - INFO - __main__ -    global_step = 10550, average loss = 0.08084082975808997
09/30/2023 18:24:06 - INFO - __main__ -    global_step = 10600, average loss = 0.077233616621088
09/30/2023 18:24:06 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 18:24:06 - INFO - __main__ -     Num examples = 10000
09/30/2023 18:24:06 - INFO - __main__ -     Batch size = 32
09/30/2023 18:28:26 - INFO - __main__ -   ***** Eval results *****
09/30/2023 18:28:26 - INFO - __main__ -     acc = 0.8219
09/30/2023 18:32:23 - INFO - __main__ -    global_step = 10650, average loss = 0.0749396042097942
09/30/2023 18:36:24 - INFO - __main__ -    global_step = 10700, average loss = 0.07035453407006571
09/30/2023 18:40:30 - INFO - __main__ -    global_step = 10750, average loss = 0.0701333080389304
09/30/2023 18:44:44 - INFO - __main__ -    global_step = 10800, average loss = 0.06815460226869618
09/30/2023 18:44:45 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 18:44:45 - INFO - __main__ -     Num examples = 10000
09/30/2023 18:44:45 - INFO - __main__ -     Batch size = 32
09/30/2023 18:49:04 - INFO - __main__ -   ***** Eval results *****
09/30/2023 18:49:04 - INFO - __main__ -     acc = 0.8246
09/30/2023 18:53:04 - INFO - __main__ -    global_step = 10850, average loss = 0.06231740675430046
09/30/2023 18:57:11 - INFO - __main__ -    global_step = 10900, average loss = 0.07749273380759406
09/30/2023 19:01:27 - INFO - __main__ -    global_step = 10950, average loss = 0.07356921623417292
09/30/2023 19:05:44 - INFO - __main__ -    global_step = 11000, average loss = 0.06861940244401922
09/30/2023 19:05:44 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 19:05:44 - INFO - __main__ -     Num examples = 10000
09/30/2023 19:05:44 - INFO - __main__ -     Batch size = 32
09/30/2023 19:10:04 - INFO - __main__ -   ***** Eval results *****
09/30/2023 19:10:04 - INFO - __main__ -     acc = 0.8237
09/30/2023 19:13:58 - INFO - __main__ -    global_step = 11050, average loss = 0.07190075869159046
09/30/2023 19:18:18 - INFO - __main__ -    global_step = 11100, average loss = 0.07798185770014243
09/30/2023 19:22:25 - INFO - __main__ -    global_step = 11150, average loss = 0.05461175944059505
09/30/2023 19:26:36 - INFO - __main__ -    global_step = 11200, average loss = 0.07214928590841736
09/30/2023 19:26:36 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 19:26:36 - INFO - __main__ -     Num examples = 10000
09/30/2023 19:26:36 - INFO - __main__ -     Batch size = 32
09/30/2023 19:30:56 - INFO - __main__ -   ***** Eval results *****
09/30/2023 19:30:56 - INFO - __main__ -     acc = 0.8281
09/30/2023 19:34:46 - INFO - __main__ -    global_step = 11250, average loss = 0.07595877689196641
09/30/2023 19:38:51 - INFO - __main__ -    global_step = 11300, average loss = 0.06289271867310163
09/30/2023 19:42:58 - INFO - __main__ -    global_step = 11350, average loss = 0.07287138866693567
09/30/2023 19:47:05 - INFO - __main__ -    global_step = 11400, average loss = 0.0736375573805708
09/30/2023 19:47:05 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 19:47:05 - INFO - __main__ -     Num examples = 10000
09/30/2023 19:47:05 - INFO - __main__ -     Batch size = 32
09/30/2023 19:51:26 - INFO - __main__ -   ***** Eval results *****
09/30/2023 19:51:26 - INFO - __main__ -     acc = 0.8265
09/30/2023 19:55:14 - INFO - __main__ -    global_step = 11450, average loss = 0.07105860608404328
09/30/2023 19:59:22 - INFO - __main__ -    global_step = 11500, average loss = 0.07589100849851092
09/30/2023 20:03:31 - INFO - __main__ -    global_step = 11550, average loss = 0.07193597211022279
09/30/2023 20:07:44 - INFO - __main__ -    global_step = 11600, average loss = 0.0786158631305443
09/30/2023 20:07:45 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 20:07:45 - INFO - __main__ -     Num examples = 10000
09/30/2023 20:07:45 - INFO - __main__ -     Batch size = 32
09/30/2023 20:12:05 - INFO - __main__ -   ***** Eval results *****
09/30/2023 20:12:05 - INFO - __main__ -     acc = 0.8224
09/30/2023 20:16:14 - INFO - __main__ -    global_step = 11650, average loss = 0.07484395604304155
09/30/2023 20:20:16 - INFO - __main__ -    global_step = 11700, average loss = 0.07182746810896788
09/30/2023 20:24:28 - INFO - __main__ -    global_step = 11750, average loss = 0.06392118992527684
09/30/2023 20:28:47 - INFO - __main__ -    global_step = 11800, average loss = 0.06359485059540021
09/30/2023 20:28:48 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 20:28:48 - INFO - __main__ -     Num examples = 10000
09/30/2023 20:28:48 - INFO - __main__ -     Batch size = 32
09/30/2023 20:33:07 - INFO - __main__ -   ***** Eval results *****
09/30/2023 20:33:07 - INFO - __main__ -     acc = 0.8225
09/30/2023 20:36:55 - INFO - __main__ -    global_step = 11850, average loss = 0.06557874951142367
09/30/2023 20:40:51 - INFO - __main__ -    global_step = 11900, average loss = 0.06787695961887948
09/30/2023 20:45:01 - INFO - __main__ -    global_step = 11950, average loss = 0.07802391385892406
09/30/2023 20:49:19 - INFO - __main__ -    global_step = 12000, average loss = 0.062383338503277624
09/30/2023 20:49:19 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 20:49:19 - INFO - __main__ -     Num examples = 10000
09/30/2023 20:49:19 - INFO - __main__ -     Batch size = 32
09/30/2023 20:53:41 - INFO - __main__ -   ***** Eval results *****
09/30/2023 20:53:41 - INFO - __main__ -     acc = 0.8221
09/30/2023 20:57:31 - INFO - __main__ -    global_step = 12050, average loss = 0.07041985652205768
09/30/2023 21:01:33 - INFO - __main__ -    global_step = 12100, average loss = 0.07904728068271652
09/30/2023 21:05:47 - INFO - __main__ -    global_step = 12150, average loss = 0.07474817682654247
09/30/2023 21:09:58 - INFO - __main__ -    global_step = 12200, average loss = 0.07402907914118259
09/30/2023 21:09:58 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 21:09:58 - INFO - __main__ -     Num examples = 10000
09/30/2023 21:09:58 - INFO - __main__ -     Batch size = 32
09/30/2023 21:14:19 - INFO - __main__ -   ***** Eval results *****
09/30/2023 21:14:19 - INFO - __main__ -     acc = 0.8327
09/30/2023 21:14:46 - INFO - __main__ -   Saving model checkpoint to output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
09/30/2023 21:18:46 - INFO - __main__ -    global_step = 12250, average loss = 0.07039213450989337
09/30/2023 21:22:59 - INFO - __main__ -    global_step = 12300, average loss = 0.0842395970186044
09/30/2023 21:27:05 - INFO - __main__ -    global_step = 12350, average loss = 0.06603515204827999
09/30/2023 21:31:22 - INFO - __main__ -    global_step = 12400, average loss = 0.06760421821546515
09/30/2023 21:31:22 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 21:31:22 - INFO - __main__ -     Num examples = 10000
09/30/2023 21:31:22 - INFO - __main__ -     Batch size = 32
09/30/2023 21:35:43 - INFO - __main__ -   ***** Eval results *****
09/30/2023 21:35:43 - INFO - __main__ -     acc = 0.8208
09/30/2023 21:39:33 - INFO - __main__ -    global_step = 12450, average loss = 0.06917047601906233
09/30/2023 21:43:44 - INFO - __main__ -    global_step = 12500, average loss = 0.07573592953915068
09/30/2023 21:48:03 - INFO - __main__ -    global_step = 12550, average loss = 0.06653125052485848
09/30/2023 21:52:22 - INFO - __main__ -    global_step = 12600, average loss = 0.06815064429247286
09/30/2023 21:52:23 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 21:52:23 - INFO - __main__ -     Num examples = 10000
09/30/2023 21:52:23 - INFO - __main__ -     Batch size = 32
09/30/2023 21:56:43 - INFO - __main__ -   ***** Eval results *****
09/30/2023 21:56:43 - INFO - __main__ -     acc = 0.819
09/30/2023 22:00:39 - INFO - __main__ -    global_step = 12650, average loss = 0.07732899946378893
09/30/2023 22:04:44 - INFO - __main__ -    global_step = 12700, average loss = 0.06547158910783764
09/30/2023 22:08:49 - INFO - __main__ -    global_step = 12750, average loss = 0.0728905378174386
09/30/2023 22:13:03 - INFO - __main__ -    global_step = 12800, average loss = 0.07366545890477937
09/30/2023 22:13:04 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 22:13:04 - INFO - __main__ -     Num examples = 10000
09/30/2023 22:13:04 - INFO - __main__ -     Batch size = 32
09/30/2023 22:17:25 - INFO - __main__ -   ***** Eval results *****
09/30/2023 22:17:25 - INFO - __main__ -     acc = 0.8182
09/30/2023 22:21:28 - INFO - __main__ -    global_step = 12850, average loss = 0.06894337675126735
09/30/2023 22:25:41 - INFO - __main__ -    global_step = 12900, average loss = 0.07351460054007475
09/30/2023 22:29:49 - INFO - __main__ -    global_step = 12950, average loss = 0.0674650944762834
09/30/2023 22:34:09 - INFO - __main__ -    global_step = 13000, average loss = 0.07850258736492834
09/30/2023 22:34:09 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 22:34:09 - INFO - __main__ -     Num examples = 10000
09/30/2023 22:34:09 - INFO - __main__ -     Batch size = 32
09/30/2023 22:38:30 - INFO - __main__ -   ***** Eval results *****
09/30/2023 22:38:30 - INFO - __main__ -     acc = 0.8321
09/30/2023 22:42:24 - INFO - __main__ -    global_step = 13050, average loss = 0.07653208828101925
09/30/2023 22:46:20 - INFO - __main__ -    global_step = 13100, average loss = 0.06802368102005857
09/30/2023 22:50:29 - INFO - __main__ -    global_step = 13150, average loss = 0.06454230795552576
09/30/2023 22:54:34 - INFO - __main__ -    global_step = 13200, average loss = 0.07258539929578546
09/30/2023 22:54:35 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 22:54:35 - INFO - __main__ -     Num examples = 10000
09/30/2023 22:54:35 - INFO - __main__ -     Batch size = 32
09/30/2023 22:58:54 - INFO - __main__ -   ***** Eval results *****
09/30/2023 22:58:54 - INFO - __main__ -     acc = 0.8252
09/30/2023 23:02:57 - INFO - __main__ -    global_step = 13250, average loss = 0.07325911161562544
09/30/2023 23:07:12 - INFO - __main__ -    global_step = 13300, average loss = 0.06880584957727479
09/30/2023 23:11:21 - INFO - __main__ -    global_step = 13350, average loss = 0.07009069720297703
09/30/2023 23:15:34 - INFO - __main__ -    global_step = 13400, average loss = 0.07083460625182852
09/30/2023 23:15:35 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 23:15:35 - INFO - __main__ -     Num examples = 10000
09/30/2023 23:15:35 - INFO - __main__ -     Batch size = 32
09/30/2023 23:19:56 - INFO - __main__ -   ***** Eval results *****
09/30/2023 23:19:56 - INFO - __main__ -     acc = 0.813
09/30/2023 23:23:55 - INFO - __main__ -    global_step = 13450, average loss = 0.06977577161625959
09/30/2023 23:27:49 - INFO - __main__ -    global_step = 13500, average loss = 0.0730690676838276
09/30/2023 23:31:51 - INFO - __main__ -    global_step = 13550, average loss = 0.07233811266596604
09/30/2023 23:35:53 - INFO - __main__ -    global_step = 13600, average loss = 0.0773136636797426
09/30/2023 23:35:54 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 23:35:54 - INFO - __main__ -     Num examples = 10000
09/30/2023 23:35:54 - INFO - __main__ -     Batch size = 32
09/30/2023 23:40:14 - INFO - __main__ -   ***** Eval results *****
09/30/2023 23:40:14 - INFO - __main__ -     acc = 0.8254
09/30/2023 23:44:18 - INFO - __main__ -    global_step = 13650, average loss = 0.0625762648001546
09/30/2023 23:48:29 - INFO - __main__ -    global_step = 13700, average loss = 0.07835062241327251
09/30/2023 23:52:47 - INFO - __main__ -    global_step = 13750, average loss = 0.06917831582177314
09/30/2023 23:57:06 - INFO - __main__ -    global_step = 13800, average loss = 0.06653823942549934
09/30/2023 23:57:07 - INFO - __main__ -   ***** Running evaluation *****
09/30/2023 23:57:07 - INFO - __main__ -     Num examples = 10000
09/30/2023 23:57:07 - INFO - __main__ -     Batch size = 32
10/01/2023 00:01:27 - INFO - __main__ -   ***** Eval results *****
10/01/2023 00:01:27 - INFO - __main__ -     acc = 0.8231
10/01/2023 00:05:24 - INFO - __main__ -    global_step = 13850, average loss = 0.07134979092643334
10/01/2023 00:09:31 - INFO - __main__ -    global_step = 13900, average loss = 0.07882154490274842
10/01/2023 00:13:33 - INFO - __main__ -    global_step = 13950, average loss = 0.067044138008132
10/01/2023 00:17:54 - INFO - __main__ -    global_step = 14000, average loss = 0.06602240080737828
10/01/2023 00:17:55 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 00:17:55 - INFO - __main__ -     Num examples = 10000
10/01/2023 00:17:55 - INFO - __main__ -     Batch size = 32
10/01/2023 00:22:16 - INFO - __main__ -   ***** Eval results *****
10/01/2023 00:22:16 - INFO - __main__ -     acc = 0.8185
10/01/2023 00:26:20 - INFO - __main__ -    global_step = 14050, average loss = 0.07546966458212409
10/01/2023 00:30:49 - INFO - __main__ -    global_step = 14100, average loss = 0.06855787578620948
10/01/2023 00:35:15 - INFO - __main__ -    global_step = 14150, average loss = 0.06737258993505747
10/01/2023 00:39:39 - INFO - __main__ -    global_step = 14200, average loss = 0.05966844407041208
10/01/2023 00:39:40 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 00:39:40 - INFO - __main__ -     Num examples = 10000
10/01/2023 00:39:40 - INFO - __main__ -     Batch size = 32
10/01/2023 00:44:00 - INFO - __main__ -   ***** Eval results *****
10/01/2023 00:44:00 - INFO - __main__ -     acc = 0.8282
10/01/2023 00:47:56 - INFO - __main__ -    global_step = 14250, average loss = 0.0709371871012263
10/01/2023 00:51:54 - INFO - __main__ -    global_step = 14300, average loss = 0.07779215545522675
10/01/2023 00:56:02 - INFO - __main__ -    global_step = 14350, average loss = 0.06590510867084959
10/01/2023 01:00:08 - INFO - __main__ -    global_step = 14400, average loss = 0.061885312875092496
10/01/2023 01:00:09 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 01:00:09 - INFO - __main__ -     Num examples = 10000
10/01/2023 01:00:09 - INFO - __main__ -     Batch size = 32
10/01/2023 01:04:29 - INFO - __main__ -   ***** Eval results *****
10/01/2023 01:04:29 - INFO - __main__ -     acc = 0.8195
10/01/2023 01:08:20 - INFO - __main__ -    global_step = 14450, average loss = 0.07757491528376705
10/01/2023 01:12:26 - INFO - __main__ -    global_step = 14500, average loss = 0.061351443203457166
10/01/2023 01:16:44 - INFO - __main__ -    global_step = 14550, average loss = 0.06742463728594884
10/01/2023 01:20:55 - INFO - __main__ -    global_step = 14600, average loss = 0.06395716872473713
10/01/2023 01:20:56 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 01:20:56 - INFO - __main__ -     Num examples = 10000
10/01/2023 01:20:56 - INFO - __main__ -     Batch size = 32
10/01/2023 01:25:16 - INFO - __main__ -   ***** Eval results *****
10/01/2023 01:25:16 - INFO - __main__ -     acc = 0.8271
10/01/2023 01:29:11 - INFO - __main__ -    global_step = 14650, average loss = 0.0680865884249215
10/01/2023 01:33:17 - INFO - __main__ -    global_step = 14700, average loss = 0.07319515083199804
10/01/2023 01:37:31 - INFO - __main__ -    global_step = 14750, average loss = 0.0750861974158397
10/01/2023 01:41:39 - INFO - __main__ -    global_step = 14800, average loss = 0.07455838610287174
10/01/2023 01:41:39 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 01:41:39 - INFO - __main__ -     Num examples = 10000
10/01/2023 01:41:39 - INFO - __main__ -     Batch size = 32
10/01/2023 01:45:59 - INFO - __main__ -   ***** Eval results *****
10/01/2023 01:45:59 - INFO - __main__ -     acc = 0.8285
10/01/2023 01:49:49 - INFO - __main__ -    global_step = 14850, average loss = 0.0746920863639025
10/01/2023 01:53:48 - INFO - __main__ -    global_step = 14900, average loss = 0.06193213762038795
10/01/2023 01:58:00 - INFO - __main__ -    global_step = 14950, average loss = 0.0684903811987897
10/01/2023 02:02:20 - INFO - __main__ -    global_step = 15000, average loss = 0.07475626632280181
10/01/2023 02:02:21 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 02:02:21 - INFO - __main__ -     Num examples = 10000
10/01/2023 02:02:21 - INFO - __main__ -     Batch size = 32
10/01/2023 02:06:40 - INFO - __main__ -   ***** Eval results *****
10/01/2023 02:06:40 - INFO - __main__ -     acc = 0.8221
10/01/2023 02:10:33 - INFO - __main__ -    global_step = 15050, average loss = 0.06398421550955391
10/01/2023 02:14:31 - INFO - __main__ -    global_step = 15100, average loss = 0.07387388837814797
10/01/2023 02:18:36 - INFO - __main__ -    global_step = 15150, average loss = 0.07215547483820046
10/01/2023 02:22:42 - INFO - __main__ -    global_step = 15200, average loss = 0.06692371807614109
10/01/2023 02:22:42 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 02:22:42 - INFO - __main__ -     Num examples = 10000
10/01/2023 02:22:42 - INFO - __main__ -     Batch size = 32
10/01/2023 02:27:06 - INFO - __main__ -   ***** Eval results *****
10/01/2023 02:27:06 - INFO - __main__ -     acc = 0.828
10/01/2023 02:31:03 - INFO - __main__ -    global_step = 15250, average loss = 0.07475481618889716
10/01/2023 02:35:03 - INFO - __main__ -    global_step = 15300, average loss = 0.06605282124131918
10/01/2023 02:39:06 - INFO - __main__ -    global_step = 15350, average loss = 0.0742860847054817
10/01/2023 02:43:08 - INFO - __main__ -    global_step = 15400, average loss = 0.06508645007126689
10/01/2023 02:43:09 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 02:43:09 - INFO - __main__ -     Num examples = 10000
10/01/2023 02:43:09 - INFO - __main__ -     Batch size = 32
10/01/2023 02:47:27 - INFO - __main__ -   ***** Eval results *****
10/01/2023 02:47:27 - INFO - __main__ -     acc = 0.8244
10/01/2023 02:51:15 - INFO - __main__ -    global_step = 15450, average loss = 0.0657403554152188
10/01/2023 02:55:25 - INFO - __main__ -    global_step = 15500, average loss = 0.06363382869447377
10/01/2023 02:59:33 - INFO - __main__ -    global_step = 15550, average loss = 0.068332606570184
10/01/2023 03:03:36 - INFO - __main__ -    global_step = 15600, average loss = 0.0638002801532275
10/01/2023 03:03:37 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 03:03:37 - INFO - __main__ -     Num examples = 10000
10/01/2023 03:03:37 - INFO - __main__ -     Batch size = 32
10/01/2023 03:07:54 - INFO - __main__ -   ***** Eval results *****
10/01/2023 03:07:54 - INFO - __main__ -     acc = 0.8245
10/01/2023 03:11:47 - INFO - __main__ -    global_step = 15650, average loss = 0.07057813088395051
10/01/2023 03:15:48 - INFO - __main__ -    global_step = 15700, average loss = 0.059586076617561046
10/01/2023 03:19:50 - INFO - __main__ -    global_step = 15750, average loss = 0.06329842852351249
10/01/2023 03:24:07 - INFO - __main__ -    global_step = 15800, average loss = 0.0673095579940309
10/01/2023 03:24:08 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 03:24:08 - INFO - __main__ -     Num examples = 10000
10/01/2023 03:24:08 - INFO - __main__ -     Batch size = 32
10/01/2023 03:28:27 - INFO - __main__ -   ***** Eval results *****
10/01/2023 03:28:27 - INFO - __main__ -     acc = 0.8191
10/01/2023 03:32:25 - INFO - __main__ -    global_step = 15850, average loss = 0.06719043602446619
10/01/2023 03:36:22 - INFO - __main__ -    global_step = 15900, average loss = 0.06470626855618321
10/01/2023 03:40:22 - INFO - __main__ -    global_step = 15950, average loss = 0.0673678615699464
10/01/2023 03:44:32 - INFO - __main__ -    global_step = 16000, average loss = 0.06654785299411742
10/01/2023 03:44:32 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 03:44:32 - INFO - __main__ -     Num examples = 10000
10/01/2023 03:44:32 - INFO - __main__ -     Batch size = 32
10/01/2023 03:48:51 - INFO - __main__ -   ***** Eval results *****
10/01/2023 03:48:51 - INFO - __main__ -     acc = 0.826
10/01/2023 03:52:42 - INFO - __main__ -    global_step = 16050, average loss = 0.07211193255971012
10/01/2023 03:56:30 - INFO - __main__ -    global_step = 16100, average loss = 0.07810956820030697
10/01/2023 04:00:37 - INFO - __main__ -    global_step = 16150, average loss = 0.07871339554849328
10/01/2023 04:04:48 - INFO - __main__ -    global_step = 16200, average loss = 0.06766451962915199
10/01/2023 04:04:48 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 04:04:48 - INFO - __main__ -     Num examples = 10000
10/01/2023 04:04:48 - INFO - __main__ -     Batch size = 32
10/01/2023 04:09:07 - INFO - __main__ -   ***** Eval results *****
10/01/2023 04:09:07 - INFO - __main__ -     acc = 0.8234
10/01/2023 04:13:00 - INFO - __main__ -    global_step = 16250, average loss = 0.07233332002186216
10/01/2023 04:17:08 - INFO - __main__ -    global_step = 16300, average loss = 0.06269402921956498
10/01/2023 04:21:18 - INFO - __main__ -    global_step = 16350, average loss = 0.066974333815524
10/01/2023 04:25:36 - INFO - __main__ -    global_step = 16400, average loss = 0.06326851320967762
10/01/2023 04:25:36 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 04:25:36 - INFO - __main__ -     Num examples = 10000
10/01/2023 04:25:36 - INFO - __main__ -     Batch size = 32
10/01/2023 04:29:55 - INFO - __main__ -   ***** Eval results *****
10/01/2023 04:29:55 - INFO - __main__ -     acc = 0.8218
10/01/2023 04:33:53 - INFO - __main__ -    global_step = 16450, average loss = 0.0583337911261151
10/01/2023 04:38:00 - INFO - __main__ -    global_step = 16500, average loss = 0.06651346774706327
10/01/2023 04:42:10 - INFO - __main__ -    global_step = 16550, average loss = 0.07442569829370768
10/01/2023 04:46:19 - INFO - __main__ -    global_step = 16600, average loss = 0.0704036247156182
10/01/2023 04:46:19 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 04:46:19 - INFO - __main__ -     Num examples = 10000
10/01/2023 04:46:19 - INFO - __main__ -     Batch size = 32
10/01/2023 04:50:38 - INFO - __main__ -   ***** Eval results *****
10/01/2023 04:50:38 - INFO - __main__ -     acc = 0.8268
10/01/2023 04:54:40 - INFO - __main__ -    global_step = 16650, average loss = 0.07102784802380484
10/01/2023 04:58:39 - INFO - __main__ -    global_step = 16700, average loss = 0.07482151540141785
10/01/2023 05:02:48 - INFO - __main__ -    global_step = 16750, average loss = 0.06266404812475229
10/01/2023 05:06:49 - INFO - __main__ -    global_step = 16800, average loss = 0.06936132206232287
10/01/2023 05:06:50 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 05:06:50 - INFO - __main__ -     Num examples = 10000
10/01/2023 05:06:50 - INFO - __main__ -     Batch size = 32
10/01/2023 05:11:07 - INFO - __main__ -   ***** Eval results *****
10/01/2023 05:11:07 - INFO - __main__ -     acc = 0.8313
10/01/2023 05:15:16 - INFO - __main__ -    global_step = 16850, average loss = 0.060352628196997105
10/01/2023 05:19:33 - INFO - __main__ -    global_step = 16900, average loss = 0.0641949670168833
10/01/2023 05:23:53 - INFO - __main__ -    global_step = 16950, average loss = 0.0711748162342701
10/01/2023 05:28:04 - INFO - __main__ -    global_step = 17000, average loss = 0.07767359625780955
10/01/2023 05:28:05 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 05:28:05 - INFO - __main__ -     Num examples = 10000
10/01/2023 05:28:05 - INFO - __main__ -     Batch size = 32
10/01/2023 05:32:22 - INFO - __main__ -   ***** Eval results *****
10/01/2023 05:32:22 - INFO - __main__ -     acc = 0.8302
10/01/2023 05:36:19 - INFO - __main__ -    global_step = 17050, average loss = 0.059951672412971675
10/01/2023 05:40:23 - INFO - __main__ -    global_step = 17100, average loss = 0.0679468241819086
10/01/2023 05:44:37 - INFO - __main__ -    global_step = 17150, average loss = 0.06287542213140114
10/01/2023 05:48:53 - INFO - __main__ -    global_step = 17200, average loss = 0.07064101672236575
10/01/2023 05:48:53 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 05:48:53 - INFO - __main__ -     Num examples = 10000
10/01/2023 05:48:53 - INFO - __main__ -     Batch size = 32
10/01/2023 05:53:11 - INFO - __main__ -   ***** Eval results *****
10/01/2023 05:53:11 - INFO - __main__ -     acc = 0.8288
10/01/2023 05:57:08 - INFO - __main__ -    global_step = 17250, average loss = 0.06821862254073494
10/01/2023 06:01:07 - INFO - __main__ -    global_step = 17300, average loss = 0.06737288911346695
10/01/2023 06:05:09 - INFO - __main__ -    global_step = 17350, average loss = 0.06524526451248676
10/01/2023 06:09:17 - INFO - __main__ -    global_step = 17400, average loss = 0.06838752188666604
10/01/2023 06:09:17 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 06:09:17 - INFO - __main__ -     Num examples = 10000
10/01/2023 06:09:17 - INFO - __main__ -     Batch size = 32
10/01/2023 06:13:34 - INFO - __main__ -   ***** Eval results *****
10/01/2023 06:13:34 - INFO - __main__ -     acc = 0.8292
10/01/2023 06:17:34 - INFO - __main__ -    global_step = 17450, average loss = 0.07033179465208378
10/01/2023 06:21:42 - INFO - __main__ -    global_step = 17500, average loss = 0.07338941472058651
10/01/2023 06:25:54 - INFO - __main__ -    global_step = 17550, average loss = 0.06760536882744418
10/01/2023 06:30:29 - INFO - __main__ -    global_step = 17600, average loss = 0.06395369231896893
10/01/2023 06:30:30 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 06:30:30 - INFO - __main__ -     Num examples = 10000
10/01/2023 06:30:30 - INFO - __main__ -     Batch size = 32
10/01/2023 06:34:46 - INFO - __main__ -   ***** Eval results *****
10/01/2023 06:34:46 - INFO - __main__ -     acc = 0.8226
10/01/2023 06:38:42 - INFO - __main__ -    global_step = 17650, average loss = 0.0788995540245378
10/01/2023 06:42:45 - INFO - __main__ -    global_step = 17700, average loss = 0.058938835552726235
10/01/2023 06:46:55 - INFO - __main__ -    global_step = 17750, average loss = 0.062029462043719834
10/01/2023 06:51:15 - INFO - __main__ -    global_step = 17800, average loss = 0.07220558329383493
10/01/2023 06:51:15 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 06:51:15 - INFO - __main__ -     Num examples = 10000
10/01/2023 06:51:15 - INFO - __main__ -     Batch size = 32
10/01/2023 06:55:33 - INFO - __main__ -   ***** Eval results *****
10/01/2023 06:55:33 - INFO - __main__ -     acc = 0.823
10/01/2023 06:59:32 - INFO - __main__ -    global_step = 17850, average loss = 0.07046543042039048
10/01/2023 07:03:39 - INFO - __main__ -    global_step = 17900, average loss = 0.0620857437804807
10/01/2023 07:07:50 - INFO - __main__ -    global_step = 17950, average loss = 0.05406381562563183
10/01/2023 07:12:05 - INFO - __main__ -    global_step = 18000, average loss = 0.05979254503792617
10/01/2023 07:12:05 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 07:12:05 - INFO - __main__ -     Num examples = 10000
10/01/2023 07:12:05 - INFO - __main__ -     Batch size = 32
10/01/2023 07:16:22 - INFO - __main__ -   ***** Eval results *****
10/01/2023 07:16:22 - INFO - __main__ -     acc = 0.8237
10/01/2023 07:20:13 - INFO - __main__ -    global_step = 18050, average loss = 0.06541542315782863
10/01/2023 07:24:31 - INFO - __main__ -    global_step = 18100, average loss = 0.06534778851972078
10/01/2023 07:28:50 - INFO - __main__ -    global_step = 18150, average loss = 0.06520377914806887
10/01/2023 07:33:09 - INFO - __main__ -    global_step = 18200, average loss = 0.05995443502964917
10/01/2023 07:33:10 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 07:33:10 - INFO - __main__ -     Num examples = 10000
10/01/2023 07:33:10 - INFO - __main__ -     Batch size = 32
10/01/2023 07:37:27 - INFO - __main__ -   ***** Eval results *****
10/01/2023 07:37:27 - INFO - __main__ -     acc = 0.825
10/01/2023 07:41:29 - INFO - __main__ -    global_step = 18250, average loss = 0.0729160438424151
10/01/2023 07:45:44 - INFO - __main__ -    global_step = 18300, average loss = 0.06983143856698007
10/01/2023 07:48:53 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 07:48:53 - INFO - __main__ -     Num examples = 10000
10/01/2023 07:48:53 - INFO - __main__ -     Batch size = 32
10/01/2023 07:53:22 - INFO - __main__ -   ***** Eval results *****
10/01/2023 07:53:22 - INFO - __main__ -     acc = 0.8249
10/01/2023 07:53:22 - INFO - __main__ -    global_step = 18336, average loss = 0.09140925639286196
10/01/2023 07:53:56 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 07:53:56 - INFO - __main__ -     Num examples = 10000
10/01/2023 07:53:56 - INFO - __main__ -     Batch size = 32
10/01/2023 07:58:24 - INFO - __main__ -   ***** Eval results *****
10/01/2023 07:58:24 - INFO - __main__ -     acc = 0.8326
10/01/2023 07:58:30 - INFO - evaluate_DeBERTa -   Namespace(dataset_file='../../../data/mcqa/eval/socialiqa_dev.jsonl', lm='output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', out_dir='./eval_results/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', device=0, reader='socialiqa', overwrite_output_dir=False, cache_dir=None)
10/01/2023 07:58:30 - INFO - evaluate_DeBERTa -   Initializing output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
10/01/2023 08:06:13 - INFO - evaluate_DeBERTa -   Namespace(dataset_file='../../../data/mcqa/eval/winogrande_dev.jsonl', lm='output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', out_dir='./eval_results/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', device=0, reader='winogrande', overwrite_output_dir=False, cache_dir=None)
10/01/2023 08:06:13 - INFO - evaluate_DeBERTa -   Initializing output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
10/01/2023 08:08:40 - INFO - evaluate_DeBERTa -   Namespace(dataset_file='../../../data/mcqa/eval/piqa_dev.jsonl', lm='output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', out_dir='./eval_results/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', device=0, reader='piqa', overwrite_output_dir=False, cache_dir=None)
10/01/2023 08:08:40 - INFO - evaluate_DeBERTa -   Initializing output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
10/01/2023 08:17:19 - INFO - evaluate_DeBERTa -   Namespace(dataset_file='../../../data/mcqa/eval/commonsenseqa_dev.jsonl', lm='output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', out_dir='./eval_results/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', device=0, reader='commonsenseqa', overwrite_output_dir=False, cache_dir=None)
10/01/2023 08:17:19 - INFO - evaluate_DeBERTa -   Initializing output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
10/01/2023 08:23:12 - INFO - evaluate_DeBERTa -   Namespace(dataset_file='../../../data/mcqa/eval/anli_dev.jsonl', lm='output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', out_dir='./eval_results/deberta-v3-large_car_2i_name_100k_seed_101_5e-6', device=0, reader='anli', overwrite_output_dir=False, cache_dir=None)
10/01/2023 08:23:12 - INFO - evaluate_DeBERTa -   Initializing output/Output_ATOMIC-pseudo-wWC/car_2i/deberta-v3-large_car_2i_name_100k_seed_101_5e-6
10/01/2023 08:28:58 - INFO - __main__ -   ***** Running evaluation *****
10/01/2023 08:28:58 - INFO - __main__ -     Num examples = 120
10/01/2023 08:28:58 - INFO - __main__ -     Batch size = 32
10/01/2023 08:29:16 - INFO - __main__ -   ***** Eval results *****
10/01/2023 08:29:16 - INFO - __main__ -     acc = 0.475