metadata
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpt2_summarization_reward_model
results: []
gpt2_summarization_reward_model
This model is a fine-tuned version of gpt2 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.6912
- Accuracy: 0.57
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- 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 |
---|---|---|---|---|
No log | 0.57 | 1 | 0.6911 | 0.58 |
No log | 1.57 | 2 | 0.6912 | 0.57 |
No log | 2.57 | 3 | 0.6912 | 0.57 |
No log | 3.57 | 4 | 0.6912 | 0.57 |
No log | 4.57 | 5 | 0.6912 | 0.57 |
Framework versions
- Transformers 4.26.0
- Pytorch 1.13.1+cu117
- Datasets 2.8.0
- Tokenizers 0.13.2