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