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 an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6344
- Precision: 0.8128
- Recall: 0.9363
- F1: 0.8702
- Accuracy: 0.8161
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: 8
- eval_batch_size: 8
- 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 |
|---|---|---|---|---|---|---|---|
| 0.578 | 0.8547 | 100 | 0.5079 | 0.8108 | 0.8824 | 0.8451 | 0.7871 |
| 0.4531 | 1.7094 | 200 | 0.4576 | 0.8462 | 0.8627 | 0.8544 | 0.8065 |
| 0.3272 | 2.5641 | 300 | 0.6344 | 0.8128 | 0.9363 | 0.8702 | 0.8161 |
Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3