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--- |
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library_name: transformers |
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license: mit |
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base_model: MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 |
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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: Bert-Contact-NLI |
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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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# Bert-Contact-NLI |
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This model is a fine-tuned version of [MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7](https://huggingface.co/MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.8520 |
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- Model Preparation Time: 0.0063 |
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- Accuracy: 0.7222 |
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- Precision: 0.7086 |
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- Recall: 0.7284 |
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- F1: 0.7134 |
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- Ratio: 0.3611 |
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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: 2e-05 |
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- train_batch_size: 8 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 16 |
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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: linear |
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- num_epochs: 5 |
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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 | Model Preparation Time | Accuracy | Precision | Recall | F1 | Ratio | |
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|:-------------:|:------:|:----:|:---------------:|:----------------------:|:--------:|:---------:|:------:|:------:|:------:| |
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| No log | 0.9895 | 47 | 0.8446 | 0.0063 | 0.6142 | 0.6097 | 0.5667 | 0.5804 | 0.5340 | |
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| No log | 2.0 | 95 | 0.7677 | 0.0063 | 0.6821 | 0.6774 | 0.6708 | 0.6636 | 0.3148 | |
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| No log | 2.9895 | 142 | 0.7705 | 0.0063 | 0.7006 | 0.6919 | 0.6740 | 0.6805 | 0.4043 | |
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| No log | 4.0 | 190 | 0.7969 | 0.0063 | 0.7006 | 0.6787 | 0.7153 | 0.6915 | 0.3951 | |
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| No log | 4.9474 | 235 | 0.8520 | 0.0063 | 0.7222 | 0.7086 | 0.7284 | 0.7134 | 0.3611 | |
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### Framework versions |
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- Transformers 4.46.2 |
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- Pytorch 2.5.1+cu121 |
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- Datasets 3.1.0 |
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- Tokenizers 0.20.3 |
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