license: mit | |
tags: | |
- generated_from_trainer | |
datasets: | |
- swag | |
metrics: | |
- accuracy | |
model-index: | |
- name: roberta-base-finetuned-swag | |
results: [] | |
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# roberta-base-finetuned-swag | |
This model is a fine-tuned version of [roberta-base](https://huggingface.co/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 | |