metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
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-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1395
- Accuracy: 0.9765
- F1: 0.9764
- Precision: 0.9764
- Recall: 0.9765
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 |
|---|---|---|---|---|---|---|---|
| 0.12 | 1.0 | 1147 | 0.1098 | 0.9610 | 0.9606 | 0.9625 | 0.9610 |
| 0.0999 | 2.0 | 2294 | 0.1056 | 0.9669 | 0.9667 | 0.9675 | 0.9669 |
| 0.053 | 3.0 | 3441 | 0.1327 | 0.9719 | 0.9718 | 0.9721 | 0.9719 |
| 0.0215 | 4.0 | 4588 | 0.1024 | 0.9767 | 0.9767 | 0.9767 | 0.9767 |
| 0.012 | 5.0 | 5735 | 0.1303 | 0.9795 | 0.9795 | 0.9795 | 0.9795 |
Framework versions
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 2.14.4
- Tokenizers 0.21.1