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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 |
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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 |
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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: 0.8941 |
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- Slot P: 0.0093 |
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- Slot R: 0.0199 |
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- Slot F1: 0.0127 |
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- Slot Exact Match: 0.0679 |
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- Intent Acc: 0.8756 |
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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: 10 |
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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 | 2.2457 | 0.0123 | 0.0064 | 0.0085 | 0.3665 | 0.7201 | |
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| 10.82 | 2.0 | 90 | 1.1090 | 0.0111 | 0.0182 | 0.0138 | 0.1756 | 0.8598 | |
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| 2.7961 | 3.0 | 135 | 0.9549 | 0.0097 | 0.0176 | 0.0125 | 0.1604 | 0.8647 | |
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| 1.7004 | 4.0 | 180 | 0.9027 | 0.0098 | 0.0193 | 0.0130 | 0.1215 | 0.8726 | |
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| 1.2198 | 5.0 | 225 | 0.8941 | 0.0093 | 0.0199 | 0.0127 | 0.0679 | 0.8756 | |
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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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