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--- |
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base_model: FacebookAI/roberta-base |
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library_name: peft |
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license: mit |
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metrics: |
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- precision |
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- recall |
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- f1 |
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- accuracy |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: roberta-base-ner-lorafinetune-runs-256-512 |
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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-base-ner-lorafinetune-runs-256-512 |
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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: 0.1474 |
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- Precision: 0.9303 |
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- Recall: 0.9563 |
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- F1: 0.9431 |
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- Accuracy: 0.9761 |
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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: 0.0004 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:| |
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| 0.1542 | 1.0 | 2643 | 0.1842 | 0.9746 | 0.9437 | 0.9589 | 0.9715 | |
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| 0.156 | 2.0 | 5286 | 0.1632 | 0.9123 | 0.9497 | 0.9306 | 0.9732 | |
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| 0.1217 | 3.0 | 7929 | 0.1474 | 0.9303 | 0.9563 | 0.9431 | 0.9761 | |
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### Framework versions |
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- PEFT 0.12.0 |
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- Transformers 4.43.3 |
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- Pytorch 2.4.1+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
