---
license: apache-2.0
library_name: peft
tags:
- trl
- reward-trainer
- generated_from_trainer
base_model: TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T
metrics:
- accuracy
model-index:
- name: layer-project
  results: []
datasets:
- hanyinwang/layer-project-reward-training
language:
- en
---

<!-- 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. -->

# layer-project

This model is a fine-tuned version of [TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T](https://huggingface.co/TinyLlama/TinyLlama-1.1B-intermediate-step-1431k-3T) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0064
- Accuracy: 1.0

## Model description

The model is fine-tuned as a reward function for RLHF finetuning.

## Intended uses & limitations

The model is trained on very limited data. 

## Training and evaluation data

[hanyinwang/layer-project-reward-training](https://huggingface.co/datasets/hanyinwang/layer-project-reward-training)


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.0365        | 1.0   | 5    | 0.0393          | 1.0      |
| 0.0142        | 2.0   | 10   | 0.0349          | 1.0      |
| 0.0228        | 3.0   | 15   | 0.0295          | 1.0      |
| 0.0157        | 4.0   | 20   | 0.0249          | 1.0      |
| 0.0153        | 5.0   | 25   | 0.0211          | 1.0      |
| 0.0117        | 6.0   | 30   | 0.0181          | 1.0      |
| 0.0072        | 7.0   | 35   | 0.0155          | 1.0      |
| 0.0121        | 8.0   | 40   | 0.0135          | 1.0      |
| 0.0097        | 9.0   | 45   | 0.0119          | 1.0      |
| 0.008         | 10.0  | 50   | 0.0106          | 1.0      |
| 0.0055        | 11.0  | 55   | 0.0095          | 1.0      |
| 0.0046        | 12.0  | 60   | 0.0087          | 1.0      |
| 0.0085        | 13.0  | 65   | 0.0081          | 1.0      |
| 0.0046        | 14.0  | 70   | 0.0076          | 1.0      |
| 0.0059        | 15.0  | 75   | 0.0072          | 1.0      |
| 0.0044        | 16.0  | 80   | 0.0069          | 1.0      |
| 0.0021        | 17.0  | 85   | 0.0067          | 1.0      |
| 0.0039        | 18.0  | 90   | 0.0066          | 1.0      |
| 0.0027        | 19.0  | 95   | 0.0065          | 1.0      |
| 0.0039        | 20.0  | 100  | 0.0064          | 1.0      |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1