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--- |
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license: mit |
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base_model: 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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- precision |
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- recall |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.2762 |
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- Accuracy: 0.7751 |
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- F1: 0.5205 |
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- Precision: 0.5180 |
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- Recall: 0.5235 |
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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: 32 |
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- eval_batch_size: 32 |
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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: 3 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.0829 | 1.0 | 612 | 1.0975 | 0.7771 | 0.6970 | 0.6937 | 0.7030 | |
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| 0.0937 | 2.0 | 1224 | 1.2088 | 0.7800 | 0.5233 | 0.5252 | 0.5219 | |
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| 0.0626 | 3.0 | 1836 | 1.2762 | 0.7751 | 0.5205 | 0.5180 | 0.5235 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.1.2 |
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- Datasets 2.19.0 |
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- Tokenizers 0.19.1 |
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