---
license: other
base_model: facebook/opt-350m
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: my_first_reward_modeling
  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. -->

# my_first_reward_modeling

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: 0.6161
- Accuracy: 0.6461

## 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: 1.41e-05
- train_batch_size: 64
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 1024
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.7387        | 0.07  | 10   | 0.6877          | 0.5700   |
| 0.6892        | 0.14  | 20   | 0.6735          | 0.5774   |
| 0.6704        | 0.21  | 30   | 0.6650          | 0.5939   |
| 0.6579        | 0.28  | 40   | 0.6563          | 0.6003   |
| 0.6542        | 0.35  | 50   | 0.6483          | 0.6111   |
| 0.6509        | 0.42  | 60   | 0.6398          | 0.6209   |
| 0.64          | 0.49  | 70   | 0.6334          | 0.6301   |
| 0.6322        | 0.56  | 80   | 0.6291          | 0.6354   |
| 0.6268        | 0.63  | 90   | 0.6253          | 0.6397   |
| 0.6254        | 0.7   | 100  | 0.6219          | 0.6401   |
| 0.6213        | 0.77  | 110  | 0.6201          | 0.6436   |
| 0.6284        | 0.83  | 120  | 0.6170          | 0.6454   |
| 0.6233        | 0.9   | 130  | 0.6160          | 0.6452   |
| 0.6192        | 0.97  | 140  | 0.6161          | 0.6461   |


### Framework versions

- Transformers 4.39.2
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2