gpt2-xl-summarization_reward_model
This model is a fine-tuned version of gpt2-xl on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.2875
- Accuracy: 0.6157
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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- total_eval_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
0.5856 | 1.0 | 1451 | 0.6854 | 0.6218 |
0.4314 | 2.0 | 2902 | 0.8053 | 0.6133 |
0.3166 | 3.0 | 4353 | 0.8060 | 0.6146 |
0.2625 | 4.0 | 5804 | 0.9857 | 0.6162 |
0.2279 | 5.0 | 7255 | 1.2875 | 0.6157 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2
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