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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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- f1 |
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model-index: |
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- name: fine_tuned_rte_XLMroberta |
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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_rte_XLMroberta |
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This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9629 |
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- Accuracy: 0.5517 |
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- F1: 0.5539 |
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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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- training_steps: 400 |
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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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| 0.6914 | 1.7241 | 50 | 0.7021 | 0.4138 | 0.2422 | |
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| 0.6881 | 3.4483 | 100 | 0.6818 | 0.5862 | 0.5833 | |
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| 0.6284 | 5.1724 | 150 | 0.6509 | 0.6207 | 0.6234 | |
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| 0.5051 | 6.8966 | 200 | 0.9063 | 0.5517 | 0.4977 | |
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| 0.3431 | 8.6207 | 250 | 1.1387 | 0.5862 | 0.5882 | |
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| 0.2236 | 10.3448 | 300 | 1.3533 | 0.5517 | 0.5539 | |
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| 0.098 | 12.0690 | 350 | 1.8198 | 0.5517 | 0.5539 | |
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| 0.0527 | 13.7931 | 400 | 1.9629 | 0.5517 | 0.5539 | |
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### Framework versions |
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- Transformers 4.41.0 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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