metadata
base_model: FacebookAI/roberta-base
library_name: peft
license: mit
metrics:
- precision
- recall
- f1
- accuracy
tags:
- generated_from_trainer
model-index:
- name: roberta-base-ner-lorafinetune-runs-256-512
results: []
roberta-base-ner-lorafinetune-runs-256-512
This model is a fine-tuned version of FacebookAI/roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1474
- Precision: 0.9303
- Recall: 0.9563
- F1: 0.9431
- Accuracy: 0.9761
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0004
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.1542 | 1.0 | 2643 | 0.1842 | 0.9746 | 0.9437 | 0.9589 | 0.9715 |
| 0.156 | 2.0 | 5286 | 0.1632 | 0.9123 | 0.9497 | 0.9306 | 0.9732 |
| 0.1217 | 3.0 | 7929 | 0.1474 | 0.9303 | 0.9563 | 0.9431 | 0.9761 |
Framework versions
- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1