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--- |
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library_name: transformers |
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license: cc-by-4.0 |
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base_model: NbAiLab/nb-bert-base |
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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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- precision |
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- recall |
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- f1 |
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model-index: |
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- name: nbbert_indirect_speech |
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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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# nbbert_indirect_speech |
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This model is a fine-tuned version of [NbAiLab/nb-bert-base](https://huggingface.co/NbAiLab/nb-bert-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.8555 |
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- Precision: 0.8632 |
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- Recall: 0.8555 |
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- F1: 0.8537 |
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- Loss: 0.6652 |
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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: 4 |
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- eval_batch_size: 4 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 8 |
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- optimizer: Use OptimizerNames.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: linear |
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- num_epochs: 20 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Precision | Recall | F1 | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------:|:------:|:------:|:---------------:| |
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| No log | 1.0 | 13 | 0.5937 | 0.6744 | 0.5937 | 0.4918 | 0.7937 | |
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| No log | 2.0 | 26 | 0.7974 | 0.8004 | 0.7974 | 0.7938 | 0.5315 | |
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| No log | 3.0 | 39 | 0.7321 | 0.7927 | 0.7321 | 0.7257 | 0.7020 | |
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| No log | 4.0 | 52 | 0.7905 | 0.7812 | 0.7905 | 0.7856 | 0.5378 | |
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| No log | 5.0 | 65 | 0.8130 | 0.8173 | 0.8130 | 0.8093 | 0.5648 | |
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| No log | 6.0 | 78 | 0.7978 | 0.7880 | 0.7978 | 0.7927 | 0.5450 | |
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| No log | 7.0 | 91 | 0.8313 | 0.8468 | 0.8313 | 0.8274 | 0.5858 | |
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| No log | 8.0 | 104 | 0.8313 | 0.8373 | 0.8313 | 0.8272 | 0.5247 | |
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| No log | 9.0 | 117 | 0.8294 | 0.8499 | 0.8294 | 0.8293 | 0.6528 | |
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| No log | 10.0 | 130 | 0.8414 | 0.8558 | 0.8414 | 0.8385 | 0.5475 | |
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| No log | 11.0 | 143 | 0.8472 | 0.8611 | 0.8472 | 0.8472 | 0.5893 | |
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| No log | 12.0 | 156 | 0.8421 | 0.8518 | 0.8421 | 0.8436 | 0.6162 | |
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| No log | 13.0 | 169 | 0.8382 | 0.8370 | 0.8382 | 0.8370 | 0.5678 | |
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| No log | 14.0 | 182 | 0.8502 | 0.8531 | 0.8502 | 0.8479 | 0.5941 | |
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| No log | 15.0 | 195 | 0.8521 | 0.8666 | 0.8521 | 0.8500 | 0.7085 | |
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| No log | 16.0 | 208 | 0.8511 | 0.8571 | 0.8511 | 0.8502 | 0.6244 | |
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| No log | 17.0 | 221 | 0.8548 | 0.8641 | 0.8548 | 0.8526 | 0.6625 | |
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| No log | 18.0 | 234 | 0.8553 | 0.8646 | 0.8553 | 0.8529 | 0.6697 | |
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| No log | 18.48 | 240 | 0.8555 | 0.8632 | 0.8555 | 0.8537 | 0.6652 | |
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### Framework versions |
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- Transformers 4.48.2 |
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- Pytorch 2.5.1+cu124 |
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- Tokenizers 0.21.0 |
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