metadata
library_name: transformers
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: test_model
results: []
test_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: 0.1597
- F1: 0.0
- Roc Auc: 0.5
- Accuracy: 0.8917
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: 0.001
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 35 | 0.1597 | 0.0 | 0.5 | 0.8917 |
| No log | 2.0 | 70 | 0.1509 | 0.0 | 0.5 | 0.8917 |
| No log | 3.0 | 105 | 0.1507 | 0.0 | 0.5 | 0.8917 |
| No log | 4.0 | 140 | 0.1506 | 0.0 | 0.5 | 0.8917 |
| No log | 5.0 | 175 | 0.1503 | 0.0 | 0.5 | 0.8917 |
Framework versions
- Transformers 4.46.3
- Pytorch 2.5.1+cu124
- Datasets 3.1.0
- Tokenizers 0.20.3