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--- |
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license: mit |
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base_model: FacebookAI/xlm-roberta-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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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: mrc-xlmr-base-dsc |
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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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# mrc-xlmr-base-dsc |
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This model is a fine-tuned version of [FacebookAI/xlm-roberta-base](https://huggingface.co/FacebookAI/xlm-roberta-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7023 |
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- Precision: 0.7109 |
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- Recall: 0.6810 |
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- F1: 0.6767 |
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- Exact Match: 0.7123 |
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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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- 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: 5 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Exact Match | |
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|:-------------:|:-----:|:-----:|:---------------:|:---------:|:------:|:------:|:-----------:| |
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| 0.7291 | 1.0 | 3180 | 0.6487 | 0.6459 | 0.5921 | 0.5958 | 0.6368 | |
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| 0.612 | 2.0 | 6360 | 0.5966 | 0.7004 | 0.6382 | 0.6449 | 0.6793 | |
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| 0.4627 | 3.0 | 9540 | 0.6061 | 0.6920 | 0.6645 | 0.6573 | 0.6949 | |
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| 0.3604 | 4.0 | 12720 | 0.6453 | 0.6895 | 0.6795 | 0.6652 | 0.7054 | |
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| 0.2852 | 5.0 | 15900 | 0.7023 | 0.7109 | 0.6810 | 0.6767 | 0.7123 | |
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### Framework versions |
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- Transformers 4.39.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.18.0 |
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- Tokenizers 0.15.2 |
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