---
library_name: peft
license: llama3.2
base_model: meta-llama/Llama-3.2-1B-Instruct
tags:
- generated_from_trainer
model-index:
- name: Llama-3.2-1B-Instruct-tuned
  results: []
datasets:
- TuringGame/TuringChat-chats
language:
- en
- de
---

<!-- 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. -->

# Llama-3.2-1B-Instruct-tuned

This model is a fine-tuned version of [meta-llama/Llama-3.2-1B-Instruct](https://huggingface.co/meta-llama/Llama-3.2-1B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2766

## 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: 0.01
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_BNB with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0      | 0    | 12.3951         |
| No log        | 0.2004 | 27   | 5.5223          |
| No log        | 0.4007 | 54   | 3.8031          |
| No log        | 0.6011 | 81   | 3.1578          |
| No log        | 0.8015 | 108  | 2.8569          |
| No log        | 1.0    | 135  | 2.6538          |
| No log        | 1.2004 | 162  | 2.4921          |
| No log        | 1.4007 | 189  | 2.3860          |
| No log        | 1.6011 | 216  | 2.3240          |
| No log        | 1.8015 | 243  | 2.2894          |
| No log        | 2.0    | 270  | 2.2766          |


### Framework versions

- PEFT 0.15.2
- Transformers 4.52.4
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.1