Tristan Thrush
update model card README.md
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---
license: mit
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: gpt2_summarization_reward_model
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. -->
# gpt2_summarization_reward_model
This model is a fine-tuned version of [gpt2](https://huggingface.co/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