---
license: other
base_model: facebook/opt-350m
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: reward_modeling_anthropic_hh_rm1e-4
  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_modeling_anthropic_hh_rm1e-4

This model is a fine-tuned version of [facebook/opt-350m](https://huggingface.co/facebook/opt-350m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6931
- Accuracy: 0.7339

## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7053        | 0.1087 | 500  | 0.6931          | 0.6148   |
| 0.6926        | 0.2174 | 1000 | 0.6931          | 0.6260   |
| 0.6912        | 0.3262 | 1500 | 0.6931          | 0.6737   |
| 0.6923        | 0.4349 | 2000 | 0.6931          | 0.6653   |
| 0.6946        | 0.5436 | 2500 | 0.6931          | 0.6698   |
| 0.6888        | 0.6523 | 3000 | 0.6931          | 0.6973   |
| 0.6963        | 0.7610 | 3500 | 0.6931          | 0.7138   |
| 0.689         | 0.8698 | 4000 | 0.6931          | 0.7124   |
| 0.6942        | 0.9785 | 4500 | 0.6931          | 0.7339   |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.4.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1