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olm-roberta-base-latest_summarization_reward_model
This model is a fine-tuned version of olm/olm-roberta-base-latest on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.7081
- Accuracy: 0.5686
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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6479 | 1.0 | 5804 | 0.6820 | 0.5636 |
| 0.601 | 2.0 | 11608 | 0.7081 | 0.5686 |
Framework versions
- Transformers 4.25.1
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
