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--- |
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license: mit |
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base_model: FacebookAI/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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- f1 |
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model-index: |
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- name: roberta-baseB_10epoch |
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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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# roberta-baseB_10epoch |
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This model is a fine-tuned version of [FacebookAI/roberta-base](https://huggingface.co/FacebookAI/roberta-base) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.1305 |
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- Accuracy: 0.8379 |
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- Precision: 0.0983 |
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- Recall: 0.0258 |
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- F1: 0.0355 |
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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: 10 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:| |
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| No log | 1.0 | 217 | 0.1250 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| No log | 2.0 | 434 | 0.1276 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| 0.1727 | 3.0 | 651 | 0.1281 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| 0.1727 | 4.0 | 868 | 0.1275 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| 0.1577 | 5.0 | 1085 | 0.1296 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| 0.1577 | 6.0 | 1302 | 0.1265 | 0.8571 | 0.0 | 0.0 | 0.0 | |
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| 0.1533 | 7.0 | 1519 | 0.1329 | 0.8529 | 0.0 | 0.0 | 0.0 | |
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| 0.1533 | 8.0 | 1736 | 0.1268 | 0.8486 | 0.0604 | 0.0037 | 0.0070 | |
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| 0.1533 | 9.0 | 1953 | 0.1292 | 0.8414 | 0.0789 | 0.0148 | 0.0221 | |
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| 0.1432 | 10.0 | 2170 | 0.1305 | 0.8379 | 0.0983 | 0.0258 | 0.0355 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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