End of training
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README.md
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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-64-1
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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-64-1
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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: 0.1432
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- Precision: 0.9517
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- Recall: 0.9598
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- F1: 0.9557
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- Accuracy: 0.9787
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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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| 0.135 | 1.0 | 2643 | 0.1693 | 0.9564 | 0.9499 | 0.9531 | 0.9741 |
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| 0.1302 | 2.0 | 5286 | 0.1486 | 0.9531 | 0.9571 | 0.9551 | 0.9776 |
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| 0.1149 | 3.0 | 7929 | 0.1432 | 0.9517 | 0.9598 | 0.9557 | 0.9787 |
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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
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