---
license: apache-2.0
base_model: EleutherAI/pythia-160m
tags:
- trl
- reward-trainer
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: rm1
  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. -->

# rm1

This model is a fine-tuned version of [EleutherAI/pythia-160m](https://huggingface.co/EleutherAI/pythia-160m) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5286
- Accuracy: 0.8456

## 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: 3e-06
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 32
- total_train_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.6883        | 0.0621 | 5    | 0.6846          | 0.7537   |
| 0.6723        | 0.1242 | 10   | 0.6717          | 0.7978   |
| 0.6761        | 0.1863 | 15   | 0.6559          | 0.8162   |
| 0.6627        | 0.2484 | 20   | 0.6379          | 0.8125   |
| 0.6156        | 0.3104 | 25   | 0.6175          | 0.8125   |
| 0.6232        | 0.3725 | 30   | 0.5937          | 0.8272   |
| 0.5985        | 0.4346 | 35   | 0.5711          | 0.8456   |
| 0.6024        | 0.4967 | 40   | 0.5549          | 0.8309   |
| 0.5906        | 0.5588 | 45   | 0.5449          | 0.8346   |
| 0.6184        | 0.6209 | 50   | 0.5383          | 0.8419   |
| 0.5379        | 0.6830 | 55   | 0.5338          | 0.8382   |
| 0.564         | 0.7451 | 60   | 0.5312          | 0.8456   |
| 0.5635        | 0.8071 | 65   | 0.5299          | 0.8456   |
| 0.5892        | 0.8692 | 70   | 0.5292          | 0.8493   |
| 0.5416        | 0.9313 | 75   | 0.5288          | 0.8456   |
| 0.5994        | 0.9934 | 80   | 0.5286          | 0.8456   |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.2.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1