End of training

README.md

@@ -18,13 +18,13 @@ should probably proofread and complete it, then remove this comment. -->
 
 # RoBERTa-ext-large-lora-chinese-finetuned-ner
 
-This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) on the None dataset.
+This model is a fine-tuned version of [hfl/chinese-roberta-wwm-ext-large](https://huggingface.co/hfl/chinese-roberta-wwm-ext-large) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Loss: 0.4289
-- Precision: 0.6182
-- Recall: 0.7329
-- F1: 0.6707
-- Accuracy: 0.9114
+- Loss: 0.3762
+- Precision: 0.6284
+- Recall: 0.7311
+- F1: 0.6759
+- Accuracy: 0.9107
 
 ## Model description
 
@@ -44,7 +44,7 @@ More information needed
 
 The following hyperparameters were used during training:
 - learning_rate: 0.001
-- train_batch_size: 4
+- train_batch_size: 8
 - eval_batch_size: 8
 - seed: 42
 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
@@ -55,16 +55,16 @@ The following hyperparameters were used during training:
 
 | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1     | Accuracy |
 |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
-| 0.4612        | 1.0   | 503  | 0.3536          | 0.4817    | 0.6412 | 0.5501 | 0.8948   |
-| 0.2925        | 2.0   | 1006 | 0.3259          | 0.5403    | 0.6772 | 0.6011 | 0.9022   |
-| 0.2391        | 3.0   | 1509 | 0.3211          | 0.5572    | 0.7301 | 0.6320 | 0.9053   |
-| 0.1966        | 4.0   | 2012 | 0.3287          | 0.5768    | 0.7238 | 0.6420 | 0.9099   |
-| 0.1644        | 5.0   | 2515 | 0.3531          | 0.5717    | 0.7362 | 0.6436 | 0.9056   |
-| 0.1312        | 6.0   | 3018 | 0.3542          | 0.5874    | 0.7158 | 0.6453 | 0.9084   |
-| 0.1067        | 7.0   | 3521 | 0.3878          | 0.5844    | 0.7266 | 0.6478 | 0.9072   |
-| 0.0862        | 8.0   | 4024 | 0.3956          | 0.6186    | 0.7304 | 0.6698 | 0.9116   |
-| 0.0681        | 9.0   | 4527 | 0.4100          | 0.6206    | 0.7261 | 0.6692 | 0.9118   |
-| 0.0595        | 10.0  | 5030 | 0.4289          | 0.6182    | 0.7329 | 0.6707 | 0.9114   |
+| 0.5112        | 1.0   | 252  | 0.3440          | 0.5005    | 0.6105 | 0.5501 | 0.8940   |
+| 0.283         | 2.0   | 504  | 0.3198          | 0.5363    | 0.6715 | 0.5963 | 0.9017   |
+| 0.2373        | 3.0   | 756  | 0.3104          | 0.5506    | 0.7216 | 0.6246 | 0.9054   |
+| 0.1995        | 4.0   | 1008 | 0.3210          | 0.5804    | 0.7236 | 0.6441 | 0.9092   |
+| 0.1678        | 5.0   | 1260 | 0.3300          | 0.5828    | 0.7140 | 0.6418 | 0.9077   |
+| 0.1435        | 6.0   | 1512 | 0.3274          | 0.5912    | 0.7173 | 0.6482 | 0.9104   |
+| 0.1206        | 7.0   | 1764 | 0.3566          | 0.5964    | 0.7351 | 0.6585 | 0.9079   |
+| 0.105         | 8.0   | 2016 | 0.3579          | 0.6065    | 0.7281 | 0.6618 | 0.9112   |
+| 0.0925        | 9.0   | 2268 | 0.3645          | 0.6148    | 0.7382 | 0.6709 | 0.9103   |
+| 0.0835        | 10.0  | 2520 | 0.3762          | 0.6284    | 0.7311 | 0.6759 | 0.9107   |
 
 
 ### Framework versions

adapter_config.json

@@ -15,7 +15,7 @@
   "megatron_core": "megatron.core",
   "modules_to_save": null,
   "peft_type": "LORA",
-  "r": 8,
+  "r": 4,
   "rank_pattern": {},
   "revision": null,
   "target_modules": [

adapter_model.safetensors

@@ -1,3 +1,3 @@
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-size 3278396
+oid sha256:ffa3b146a3741354be49d9099633c44f148c1d20b98e0ae79a88d1fbd1b56527
+size 1705460

training_args.bin

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+oid sha256:4e4e412ff8e49031517fc5259b320a25814644421ae5afcc22ed00b6239a3410
 size 4600