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README.md
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---
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license: mit
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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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- recall
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- precision
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model-index:
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- name: pulf-classifier_roberta_final
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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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# pulf-classifier_roberta_final
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This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.0165
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- Accuracy: 0.9954
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- F1-score: 0.9909
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- Recall: 0.9917
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- Precision: 0.9902
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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: 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: 3
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1-score | Recall | Precision |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:--------:|:------:|:---------:|
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| 0.0248 | 1.0 | 10746 | 0.0204 | 0.9937 | 0.9875 | 0.9859 | 0.9891 |
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| 0.0228 | 2.0 | 21492 | 0.0152 | 0.9963 | 0.9926 | 0.9906 | 0.9946 |
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| 0.0201 | 3.0 | 32238 | 0.0165 | 0.9954 | 0.9909 | 0.9917 | 0.9902 |
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### Framework versions
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- Transformers 4.28.1
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- Pytorch 2.0.0+cu118
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- Datasets 2.11.0
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- Tokenizers 0.13.3
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