metadata
library_name: transformers
license: mit
base_model: FacebookAI/roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: FacebookAI_roberta-large_custom_data
results: []
FacebookAI_roberta-large_custom_data
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: 0.3779
- Precision Macro: 0.8141
- Recall Macro: 0.8170
- F1 Macro: 0.8155
- Accuracy: 0.8117
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: 16
- eval_batch_size: 16
- 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 Macro | Recall Macro | F1 Macro | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.5113 | 1.0 | 270 | 0.3779 | 0.8141 | 0.8170 | 0.8155 | 0.8117 |
| 0.3962 | 2.0 | 540 | 0.4214 | 0.8266 | 0.8093 | 0.8125 | 0.8200 |
| 0.2556 | 3.0 | 810 | 0.4619 | 0.8149 | 0.8106 | 0.8112 | 0.8135 |
Framework versions
- Transformers 4.48.0
- Pytorch 2.5.1
- Datasets 3.2.0
- Tokenizers 0.21.0