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training latge t5 comment 2 code done 12/22/2023, 05:25:03

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README.md ADDED
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+ ---
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+ license: bsd-3-clause
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+ base_model: Salesforce/codet5p-220m
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+ tags:
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+ - generated_from_trainer
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+ model-index:
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+ - name: SolCoderFuncs
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+ results: []
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+ ---
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+
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+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
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+ should probably proofread and complete it, then remove this comment. -->
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+
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+ # SolCoderFuncs
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+
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+ This model is a fine-tuned version of [Salesforce/codet5p-220m](https://huggingface.co/Salesforce/codet5p-220m) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.5510
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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+ The following hyperparameters were used during training:
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+ - learning_rate: 0.0001
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+ - train_batch_size: 37
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+ - eval_batch_size: 37
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+ - seed: 100
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+ - distributed_type: multi-GPU
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+ - num_devices: 4
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+ - total_train_batch_size: 148
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+ - total_eval_batch_size: 148
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+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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+ - lr_scheduler_type: linear
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+ - num_epochs: 20
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss |
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+ |:-------------:|:-----:|:-----:|:---------------:|
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+ | 0.8793 | 1.0 | 3600 | 0.7881 |
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+ | 0.7622 | 2.0 | 7200 | 0.7190 |
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+ | 0.7077 | 3.0 | 10800 | 0.6769 |
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+ | 0.659 | 4.0 | 14400 | 0.6518 |
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+ | 0.6212 | 5.0 | 18000 | 0.6300 |
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+ | 0.589 | 6.0 | 21600 | 0.6119 |
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+ | 0.562 | 7.0 | 25200 | 0.6014 |
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+ | 0.5361 | 8.0 | 28800 | 0.5905 |
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+ | 0.5171 | 9.0 | 32400 | 0.5799 |
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+ | 0.4973 | 10.0 | 36000 | 0.5747 |
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+ | 0.4772 | 11.0 | 39600 | 0.5666 |
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+ | 0.4619 | 12.0 | 43200 | 0.5610 |
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+ | 0.4443 | 13.0 | 46800 | 0.5588 |
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+ | 0.4335 | 14.0 | 50400 | 0.5571 |
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+ | 0.4192 | 15.0 | 54000 | 0.5534 |
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+ | 0.4062 | 16.0 | 57600 | 0.5512 |
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+ | 0.3977 | 17.0 | 61200 | 0.5513 |
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+ | 0.3864 | 18.0 | 64800 | 0.5515 |
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+ | 0.3791 | 19.0 | 68400 | 0.5507 |
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+ | 0.3718 | 20.0 | 72000 | 0.5510 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.33.0
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+ - Pytorch 2.1.0+cu121
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+ - Datasets 2.11.0
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+ - Tokenizers 0.13.3
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+ {
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+ "_name_or_path": "Salesforce/codet5p-220m",
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+ "architectures": [
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+ "T5ForConditionalGeneration"
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+ ],
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+ "bos_token_id": 1,
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+ "classifier_dropout": 0.0,
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+ "d_kv": 64,
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+ "dense_act_fn": "relu",
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+ "dropout_rate": 0.1,
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+ "eos_token_id": 2,
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+ "feed_forward_proj": "relu",
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+ "initializer_factor": 1.0,
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+ "is_encoder_decoder": true,
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+ "is_gated_act": false,
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+ "layer_norm_epsilon": 1e-06,
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+ "model_type": "t5",
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+ "n_positions": 512,
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+ "num_decoder_layers": 12,
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+ "num_heads": 12,
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+ "num_layers": 12,
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+ "output_past": true,
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+ "pad_token_id": 0,
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+ "relative_attention_max_distance": 128,
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+ "relative_attention_num_buckets": 32,
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+ "torch_dtype": "float32",
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+ "transformers_version": "4.33.0",
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+ "use_cache": true,
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+ "vocab_size": 32100
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+ }
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