| --- |
| tags: |
| - generated_from_trainer |
| metrics: |
| - accuracy |
| - f1 |
| - precision |
| - recall |
| model-index: |
| - name: patentClassfication2 |
| results: [] |
| --- |
| |
| <!-- This model card has been generated automatically according to the information the Trainer had access to. You |
| should probably proofread and complete it, then remove this comment. --> |
|
|
| # patentClassfication2 |
|
|
| This model was trained from scratch on the None dataset. |
| It achieves the following results on the evaluation set: |
| - Loss: 0.5108 |
| - Accuracy: 0.7492 |
| - F1: 0.7710 |
| - Precision: 0.7025 |
| - Recall: 0.8543 |
|
|
| ## Model description |
|
|
| More information needed |
|
|
| ## Intended uses & limitations |
|
|
| More information needed |
|
|
| ## Training and evaluation data |
|
|
| More information needed |
|
|
| ## Training procedure |
|
|
| ### Training hyperparameters |
|
|
| The following hyperparameters were used during training: |
| - learning_rate: 2.329139e-05 |
| - train_batch_size: 32 |
| - eval_batch_size: 8 |
| - seed: 18 |
| - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
| - lr_scheduler_type: cosine |
| - lr_scheduler_warmup_ratio: 0.1 |
| - lr_scheduler_warmup_steps: 478 |
| - num_epochs: 11 |
|
|
| ### Training results |
|
|
| | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
| |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
| | 0.5264 | 1.0 | 1110 | 0.5108 | 0.7492 | 0.7710 | 0.7025 | 0.8543 | |
| | 0.4405 | 2.0 | 2220 | 0.5624 | 0.7463 | 0.7295 | 0.7710 | 0.6923 | |
| | 0.2972 | 3.0 | 3330 | 0.7480 | 0.7394 | 0.7224 | 0.7629 | 0.6859 | |
| | 0.1733 | 4.0 | 4440 | 0.7975 | 0.7328 | 0.7316 | 0.7266 | 0.7367 | |
| | 0.1242 | 5.0 | 5550 | 1.3035 | 0.7314 | 0.7396 | 0.7101 | 0.7716 | |
| | 0.0866 | 6.0 | 6660 | 1.6628 | 0.7272 | 0.7110 | 0.7464 | 0.6788 | |
| | 0.0493 | 7.0 | 7770 | 1.7728 | 0.7321 | 0.7285 | 0.7297 | 0.7274 | |
| | 0.0313 | 8.0 | 8880 | 2.0279 | 0.7383 | 0.7325 | 0.7402 | 0.7249 | |
| | 0.0187 | 9.0 | 9990 | 2.1956 | 0.7375 | 0.7445 | 0.7173 | 0.7739 | |
| | 0.0148 | 10.0 | 11100 | 2.2491 | 0.7355 | 0.7366 | 0.7256 | 0.7479 | |
| | 0.0129 | 11.0 | 12210 | 2.2694 | 0.7350 | 0.7378 | 0.7220 | 0.7543 | |
|
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|
|
| ### Framework versions |
|
|
| - Transformers 4.31.0 |
| - Pytorch 2.0.0 |
| - Datasets 2.14.4 |
| - Tokenizers 0.13.3 |
|
|
