metadata
library_name: transformers
license: mit
base_model: roberta-large
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: roberta-large-binary-classification
results: []
roberta-large-binary-classification
This model is a fine-tuned version of roberta-large on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6983
- Accuracy: 0.7580
- F1 Macro: 0.7453
- Precision Macro: 0.7498
- Recall Macro: 0.7425
- Auc: 0.7941
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 OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | Precision Macro | Recall Macro | Auc |
|---|---|---|---|---|---|---|---|---|
| No log | 1.0 | 79 | 0.6751 | 0.5955 | 0.3733 | 0.2978 | 0.5 | 0.6194 |
| No log | 2.0 | 158 | 0.6642 | 0.5955 | 0.3733 | 0.2978 | 0.5 | 0.6210 |
| No log | 3.0 | 237 | 0.5609 | 0.7102 | 0.6895 | 0.7003 | 0.6859 | 0.7701 |
| No log | 4.0 | 316 | 0.5676 | 0.7070 | 0.6907 | 0.6954 | 0.6883 | 0.7734 |
| No log | 5.0 | 395 | 0.6983 | 0.7580 | 0.7453 | 0.7498 | 0.7425 | 0.7941 |
| No log | 6.0 | 474 | 0.7766 | 0.7420 | 0.7319 | 0.7322 | 0.7316 | 0.7802 |
| 0.4887 | 7.0 | 553 | 1.1879 | 0.7452 | 0.7266 | 0.7399 | 0.7217 | 0.7761 |
| 0.4887 | 8.0 | 632 | 1.6676 | 0.7484 | 0.7242 | 0.7504 | 0.7180 | 0.7789 |
| 0.4887 | 9.0 | 711 | 1.6440 | 0.7548 | 0.7364 | 0.7511 | 0.7310 | 0.7889 |
| 0.4887 | 10.0 | 790 | 1.7092 | 0.7548 | 0.7364 | 0.7511 | 0.7310 | 0.7928 |
Framework versions
- Transformers 4.57.1
- Pytorch 2.8.0+cu126
- Datasets 4.0.0
- Tokenizers 0.22.1