counterbench-roberta-base
This model is a fine-tuned version of roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4148
- Accuracy: 0.8424
- Macro F1: 0.8384
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: 32
- 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
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Macro F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 62 | 0.6750 | 0.5576 | 0.3580 |
| No log | 2.0 | 124 | 0.5457 | 0.7515 | 0.7229 |
| No log | 3.0 | 186 | 0.4109 | 0.8061 | 0.8029 |
| No log | 4.0 | 248 | 0.4213 | 0.8121 | 0.8027 |
| No log | 5.0 | 310 | 0.4148 | 0.8424 | 0.8384 |
Framework versions
- Transformers 5.17.0
- Pytorch 2.14.0+cu130
- Datasets 3.6.0
- Tokenizers 0.23.2