metadata
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: roberta-base_gpt-4o-2024-05-13_gpt-4o-mini-2024-07-18_20240913_044355
results: []
roberta-base_gpt-4o-2024-05-13_gpt-4o-mini-2024-07-18_20240913_044355
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4503
- Accuracy: 0.8026
- F1: 0.8832
- Precision: 0.8292
- Recall: 0.9448
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: 32
- eval_batch_size: 8
- seed: 420
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4781 | 1.0 | 871 | 0.4503 | 0.8026 | 0.8832 | 0.8292 | 0.9448 |
| 0.4526 | 2.0 | 1742 | 0.4536 | 0.8048 | 0.8822 | 0.8434 | 0.9248 |
| 0.424 | 3.0 | 2613 | 0.4529 | 0.8052 | 0.8837 | 0.8362 | 0.9370 |
| 0.3789 | 4.0 | 3484 | 0.4970 | 0.8029 | 0.8826 | 0.8336 | 0.9379 |
| 0.3275 | 5.0 | 4355 | 0.5587 | 0.7945 | 0.8777 | 0.8286 | 0.9330 |
Framework versions
- Transformers 4.40.2
- Pytorch 2.4.1+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1