---
base_model: ChaiML/reward_models_100_170000000_cp_498032
tags:
- generated_from_trainer
model-index:
- name: 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. -->

# reward-model

This model is a fine-tuned version of [ChaiML/reward_models_100_170000000_cp_498032](https://huggingface.co/ChaiML/reward_models_100_170000000_cp_498032) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5733

## 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: 1e-05
- train_batch_size: 3
- eval_batch_size: 3
- seed: 7
- gradient_accumulation_steps: 16
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 200
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.5918        | 0.12  | 200  | 0.6011          |
| 0.5998        | 0.24  | 400  | 0.5911          |
| 0.59          | 0.36  | 600  | 0.5863          |
| 0.585         | 0.49  | 800  | 0.5823          |
| 0.5646        | 0.61  | 1000 | 0.5803          |
| 0.6048        | 0.73  | 1200 | 0.5773          |
| 0.6041        | 0.85  | 1400 | 0.5784          |
| 0.5694        | 0.97  | 1600 | 0.5747          |
| 0.5855        | 1.09  | 1800 | 0.5767          |
| 0.5764        | 1.22  | 2000 | 0.5764          |
| 0.5606        | 1.34  | 2200 | 0.5799          |
| 0.5583        | 1.46  | 2400 | 0.5778          |
| 0.5656        | 1.58  | 2600 | 0.5731          |
| 0.5812        | 1.7   | 2800 | 0.5747          |
| 0.5911        | 1.82  | 3000 | 0.5731          |
| 0.5771        | 1.94  | 3200 | 0.5733          |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.0.1+cu117
- Datasets 2.15.0
- Tokenizers 0.15.0