metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: trainer_output
results: []
trainer_output
This model is a fine-tuned version of FacebookAI/roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1273
- Accuracy: 0.9751
- F1: 0.9751
- Precision: 0.9751
- Recall: 0.9751
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: 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
- lr_scheduler_warmup_steps: 573
- num_epochs: 5
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.1262 | 1.0 | 1147 | 0.1067 | 0.9618 | 0.9618 | 0.9618 | 0.9618 |
| 0.0909 | 2.0 | 2294 | 0.1082 | 0.9656 | 0.9653 | 0.9665 | 0.9656 |
| 0.0688 | 3.0 | 3441 | 0.0899 | 0.9727 | 0.9727 | 0.9729 | 0.9727 |
| 0.0435 | 4.0 | 4588 | 0.0971 | 0.9769 | 0.9769 | 0.9769 | 0.9769 |
| 0.0405 | 5.0 | 5735 | 0.1163 | 0.9771 | 0.9771 | 0.9771 | 0.9771 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1