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---
license: mit
tags:
- generated_from_trainer
datasets:
- swag
metrics:
- accuracy
model-index:
- name: roberta-base-finetuned-swag
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# 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: 0.4753
- Accuracy: 0.8242
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.45 | 1.0 | 2298 | 1.3857 | 0.4485 |
| 0.3628 | 2.0 | 4596 | 0.4802 | 0.8163 |
| 0.1821 | 3.0 | 6894 | 0.4753 | 0.8242 |
### Framework versions
- Transformers 4.20.1
- Pytorch 1.10.0+cpu
- Datasets 2.7.1
- Tokenizers 0.12.1
|