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--- |
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license: mit |
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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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- f1 |
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model-index: |
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- name: fine-tuned-NLI-idk-mrc-nli-drop-with-xlm-roberta-large |
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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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# fine-tuned-NLI-idk-mrc-nli-drop-with-xlm-roberta-large |
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This model is a fine-tuned version of [xlm-roberta-large](https://huggingface.co/xlm-roberta-large) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0842 |
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- Accuracy: 0.9791 |
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- F1: 0.9791 |
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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: 1e-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: 16 |
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- total_train_batch_size: 128 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:| |
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| 1.252 | 0.5 | 39 | 0.6815 | 0.5288 | 0.3962 | |
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| 0.727 | 1.0 | 78 | 0.1220 | 0.9647 | 0.9646 | |
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| 0.2545 | 1.5 | 117 | 0.0908 | 0.9751 | 0.9751 | |
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| 0.1242 | 2.0 | 156 | 0.0785 | 0.9791 | 0.9791 | |
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| 0.1242 | 2.5 | 195 | 0.0773 | 0.9699 | 0.9699 | |
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| 0.0866 | 3.0 | 234 | 0.0718 | 0.9817 | 0.9817 | |
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| 0.0636 | 3.5 | 273 | 0.0827 | 0.9699 | 0.9699 | |
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| 0.0467 | 4.0 | 312 | 0.0658 | 0.9777 | 0.9777 | |
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| 0.0426 | 4.5 | 351 | 0.0842 | 0.9791 | 0.9791 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu117 |
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- Datasets 2.2.0 |
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- Tokenizers 0.13.2 |
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