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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_crf_v2 |
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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_crf_v2 |
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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: 5.5963 |
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- Slot P: 0.0077 |
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- Slot R: 0.0082 |
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- Slot F1: 0.0079 |
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- Slot Exact Match: 0.3246 |
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- Intent Acc: 0.8751 |
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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 | 15.8863 | 0.0 | 0.0 | 0.0 | 0.4088 | 0.0733 | |
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| 69.6998 | 2.0 | 90 | 7.8039 | 0.0080 | 0.0076 | 0.0078 | 0.3438 | 0.5032 | |
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| 22.3589 | 3.0 | 135 | 4.5345 | 0.0091 | 0.0100 | 0.0095 | 0.3227 | 0.7846 | |
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| 10.4218 | 4.0 | 180 | 4.0667 | 0.0110 | 0.0111 | 0.0111 | 0.3384 | 0.8406 | |
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| 6.8199 | 5.0 | 225 | 3.8871 | 0.0092 | 0.0100 | 0.0096 | 0.3261 | 0.8623 | |
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| 5.4068 | 6.0 | 270 | 3.9234 | 0.0106 | 0.0117 | 0.0111 | 0.3212 | 0.8633 | |
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| 4.2552 | 7.0 | 315 | 4.0332 | 0.0115 | 0.0129 | 0.0122 | 0.3168 | 0.8657 | |
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| 3.5197 | 8.0 | 360 | 4.2753 | 0.0080 | 0.0088 | 0.0084 | 0.3222 | 0.8647 | |
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| 2.8374 | 9.0 | 405 | 4.6031 | 0.0099 | 0.0106 | 0.0102 | 0.3256 | 0.8701 | |
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| 2.2784 | 10.0 | 450 | 4.7992 | 0.0118 | 0.0129 | 0.0123 | 0.3237 | 0.8652 | |
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| 2.2784 | 11.0 | 495 | 5.0575 | 0.0118 | 0.0129 | 0.0123 | 0.3222 | 0.8652 | |
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| 1.8204 | 12.0 | 540 | 5.1371 | 0.0088 | 0.0094 | 0.0091 | 0.3266 | 0.8731 | |
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| 1.5073 | 13.0 | 585 | 5.4768 | 0.0109 | 0.0123 | 0.0116 | 0.3133 | 0.8677 | |
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| 1.275 | 14.0 | 630 | 5.5963 | 0.0077 | 0.0082 | 0.0079 | 0.3246 | 0.8751 | |
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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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