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--- |
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library_name: transformers |
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license: apache-2.0 |
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base_model: uitnlp/CafeBERT |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: CafeBERT_massive_v3 |
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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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# CafeBERT_massive_v3 |
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This model is a fine-tuned version of [uitnlp/CafeBERT](https://huggingface.co/uitnlp/CafeBERT) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 5.2297 |
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- Slot P: 0.7256 |
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- Slot R: 0.7801 |
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- Slot F1: 0.7519 |
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- Slot Exact Match: 0.7260 |
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- Intent Acc: 0.8633 |
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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: 5e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 256 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: cosine |
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- lr_scheduler_warmup_ratio: 0.06 |
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- num_epochs: 30 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Slot P | Slot R | Slot F1 | Slot Exact Match | Intent Acc | |
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|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:-------:|:----------------:|:----------:| |
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| No log | 1.0 | 45 | 16.4744 | 0.2572 | 0.0801 | 0.1222 | 0.3114 | 0.0930 | |
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| 72.336 | 2.0 | 90 | 6.6272 | 0.5583 | 0.6075 | 0.5818 | 0.5268 | 0.6021 | |
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| 20.704 | 3.0 | 135 | 4.4083 | 0.6449 | 0.7338 | 0.6865 | 0.6596 | 0.7885 | |
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| 9.4202 | 4.0 | 180 | 3.7185 | 0.6867 | 0.7493 | 0.7166 | 0.6926 | 0.8367 | |
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| 6.3529 | 5.0 | 225 | 3.6662 | 0.7024 | 0.7726 | 0.7358 | 0.7083 | 0.8647 | |
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| 4.7787 | 6.0 | 270 | 3.8379 | 0.7102 | 0.7657 | 0.7369 | 0.7122 | 0.8667 | |
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| 3.6929 | 7.0 | 315 | 3.7687 | 0.7152 | 0.7796 | 0.7460 | 0.7191 | 0.8652 | |
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| 2.9663 | 8.0 | 360 | 4.1024 | 0.7037 | 0.7905 | 0.7446 | 0.7186 | 0.8677 | |
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| 2.4189 | 9.0 | 405 | 4.2478 | 0.7177 | 0.7856 | 0.7501 | 0.7206 | 0.8692 | |
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| 1.9492 | 10.0 | 450 | 4.4022 | 0.7179 | 0.7801 | 0.7477 | 0.7275 | 0.8697 | |
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| 1.9492 | 11.0 | 495 | 4.6437 | 0.7095 | 0.7751 | 0.7408 | 0.7122 | 0.8706 | |
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| 1.5099 | 12.0 | 540 | 4.7049 | 0.7223 | 0.7881 | 0.7537 | 0.7290 | 0.8706 | |
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| 1.2818 | 13.0 | 585 | 4.9417 | 0.7189 | 0.7811 | 0.7487 | 0.7245 | 0.8677 | |
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| 1.0546 | 14.0 | 630 | 5.0501 | 0.7188 | 0.7781 | 0.7473 | 0.7226 | 0.8667 | |
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| 0.8641 | 15.0 | 675 | 5.2297 | 0.7256 | 0.7801 | 0.7519 | 0.7260 | 0.8633 | |
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### Framework versions |
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- Transformers 4.55.0 |
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- Pytorch 2.7.0+cu126 |
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- Datasets 3.6.0 |
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- Tokenizers 0.21.4 |
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