roberta-large-sst2
This model is a fine-tuned version of roberta-large on the glue dataset. It achieves the following results on the evaluation set:
- Loss: 0.1400
- Accuracy: 0.9644
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: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- distributed_type: sagemaker_data_parallel
- num_devices: 8
- total_train_batch_size: 256
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.3688 | 1.0 | 264 | 0.1444 | 0.9564 |
| 0.1529 | 2.0 | 528 | 0.1502 | 0.9518 |
| 0.107 | 3.0 | 792 | 0.1388 | 0.9530 |
| 0.0666 | 4.0 | 1056 | 0.1400 | 0.9644 |
Framework versions
- Transformers 4.17.0
- Pytorch 1.10.2+cu113
- Datasets 1.18.4
- Tokenizers 0.11.6