metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: fintunned-v2-roberta
results: []
fintunned-v2-roberta
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2012
- Accuracy: 0.95
- F1: 0.9504
- Precision: 0.9517
- Recall: 0.9498
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: 5e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 2.3929 | 0.45 | 50 | 2.2723 | 0.2773 | 0.1892 | 0.2335 | 0.2947 |
| 1.2165 | 0.91 | 100 | 0.4612 | 0.8818 | 0.8839 | 0.8978 | 0.8825 |
| 0.3732 | 1.36 | 150 | 0.3472 | 0.9045 | 0.9058 | 0.9092 | 0.9060 |
| 0.3306 | 1.82 | 200 | 0.3077 | 0.9227 | 0.9249 | 0.9267 | 0.9250 |
| 0.2537 | 2.27 | 250 | 0.2419 | 0.9273 | 0.9281 | 0.9290 | 0.9291 |
| 0.0997 | 2.73 | 300 | 0.2012 | 0.95 | 0.9504 | 0.9517 | 0.9498 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1