roberta-base-finetuned-swag
This model is a fine-tuned version of roberta-base on the swag dataset. It achieves the following results on the evaluation set:
- Loss: 0.4382
- Accuracy: 0.8390
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: IPU
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- total_eval_batch_size: 40
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- training precision: Mixed Precision
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.5707 | 1.0 | 574 | 0.4990 | 0.8097 |
| 0.5092 | 2.0 | 1148 | 0.4321 | 0.8361 |
| 0.3597 | 3.0 | 1722 | 0.4382 | 0.8390 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.0+cpu
- Datasets 2.7.1
- Tokenizers 0.12.1