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: 0.5161
- Accuracy: 0.8266
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: 32
- total_eval_batch_size: 10
- 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 |
|---|---|---|---|---|
| 1.1273 | 1.0 | 2298 | 0.5415 | 0.7898 |
| 0.2373 | 2.0 | 4596 | 0.4756 | 0.8175 |
| 0.1788 | 3.0 | 6894 | 0.5161 | 0.8266 |
Framework versions
- Transformers 4.20.1
- Pytorch 1.10.0+cpu
- Datasets 2.7.1
- Tokenizers 0.12.1
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