README.md

---
base_model: unsloth/meta-llama-3.1-8b-instruct-bnb-4bit
library_name: peft
license: llama3.1
tags:
- trl
- sft
- unsloth
- generated_from_trainer
model-index:
- name: meta-llama-Meta-Llama-3.1-8B-Instruct_SFT_E1_D30003
  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. -->

[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/nicola-er-ho/clembench-playpen-sft/runs/ojtaq980)
# meta-llama-Meta-Llama-3.1-8B-Instruct_SFT_E1_D30003

This model is a fine-tuned version of [unsloth/meta-llama-3.1-8b-instruct-bnb-4bit](https://huggingface.co/unsloth/meta-llama-3.1-8b-instruct-bnb-4bit) on the None dataset.

## Model description

This model was trained on Successful episodes of the top 3 model similar to [D20002](clembench-playpen/meta-llama-Meta-Llama-3.1-8B-Instruct_SFT_E1_D20002) but instead of using the whole episode as input,
each episode was split into conversation pieces. 

e.g. 
```json
[
{
  role: 'user'
  content: '...'
},
{
  role: 'assistant'
  content: '...'
},
{
  role: 'user'
  content: '...'
},
{
  role: 'assistant'
  content: '...'
},
]
```

```json
is split int:

[
{
  role: 'user'
  content: '...'
},
{
  role: 'assistant'
  content: '...'
},
```

and

```json
[
{
  role: 'user'
  content: '...'
},
{
  role: 'assistant'
  content: '...'
},
{
  role: 'user'
  content: '...'
},
{
  role: 'assistant'
  content: '...'
},
]
```

## Training and evaluation data

After splitting, the dataset contains about 4122 conversation bits accross all games.

The Dataset ID is D30003

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0002
- train_batch_size: 4
- eval_batch_size: 8
- seed: 7331
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.03
- lr_scheduler_warmup_steps: 5
- num_epochs: 1

### Training results



### Framework versions

- PEFT 0.12.0
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1