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--- |
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license: mit |
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base_model: xlm-roberta-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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model-index: |
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- name: xlm-roberta-base-finetuned-detests-wandb24 |
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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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# xlm-roberta-base-finetuned-detests-wandb24 |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/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: 0.4371 |
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- Accuracy: 0.7938 |
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- F1-score: 0.7241 |
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- Precision: 0.7136 |
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- Recall: 0.7396 |
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- Auc: 0.7396 |
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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: 16 |
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- eval_batch_size: 16 |
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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: 2 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Precision | Recall | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:---------:|:------:|:------:| |
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| 0.458 | 1.0 | 153 | 0.4512 | 0.7725 | 0.4358 | 0.3863 | 0.5 | 0.5 | |
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| 0.4262 | 2.0 | 306 | 0.4371 | 0.7938 | 0.7241 | 0.7136 | 0.7396 | 0.7396 | |
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### Framework versions |
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- Transformers 4.37.2 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.17.0 |
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- Tokenizers 0.15.1 |
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