metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: model
results: []
model
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5440
- Precision: 0.3143
- Recall: 0.2170
- F1: 0.2568
- Accuracy: 0.8900
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2733 | 0.4292 | 100 | 0.4491 | 0.3382 | 0.1454 | 0.2033 | 0.9003 |
| 0.2635 | 0.8584 | 200 | 0.4566 | 0.3327 | 0.1848 | 0.2377 | 0.8962 |
| 0.202 | 1.2876 | 300 | 0.5266 | 0.3377 | 0.1599 | 0.2171 | 0.8990 |
| 0.1981 | 1.7167 | 400 | 0.5384 | 0.3529 | 0.1495 | 0.2101 | 0.9016 |
| 0.1904 | 2.1459 | 500 | 0.5169 | 0.3004 | 0.2399 | 0.2667 | 0.8846 |
| 0.1682 | 2.5751 | 600 | 0.5660 | 0.3339 | 0.1963 | 0.2472 | 0.8954 |
Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0