---
library_name: transformers
license: llama3.2
base_model: NousResearch/Llama-3.2-1B
tags:
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrachat_200k
model-index:
- name: llama-3-2-1b-sft
  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. -->

# llama-3-2-1b-sft

This model is a fine-tuned version of [NousResearch/Llama-3.2-1B](https://huggingface.co/NousResearch/Llama-3.2-1B) on the HuggingFaceH4/ultrachat_200k dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2759

See the training yaml https://github.com/wassname/SimPO/blob/main/training_configs/llama-3-2-1b-base-sft.yaml

## 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: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.3663        | 0.0534 | 200  | 1.3955          |
| 1.3413        | 0.1069 | 400  | 1.3722          |
| 1.365         | 0.1603 | 600  | 1.3632          |
| 1.33          | 0.2138 | 800  | 1.3532          |
| 1.3219        | 0.2672 | 1000 | 1.3463          |
| 1.3355        | 0.3207 | 1200 | 1.3391          |
| 1.334         | 0.3741 | 1400 | 1.3305          |
| 1.3183        | 0.4276 | 1600 | 1.3233          |
| 1.334         | 0.4810 | 1800 | 1.3161          |
| 1.3013        | 0.5345 | 2000 | 1.3087          |
| 1.3156        | 0.5879 | 2200 | 1.3016          |
| 1.3092        | 0.6414 | 2400 | 1.2953          |
| 1.2518        | 0.6948 | 2600 | 1.2895          |
| 1.2617        | 0.7483 | 2800 | 1.2846          |
| 1.3041        | 0.8017 | 3000 | 1.2809          |
| 1.3102        | 0.8552 | 3200 | 1.2781          |
| 1.2675        | 0.9086 | 3400 | 1.2765          |
| 1.2978        | 0.9621 | 3600 | 1.2759          |


### Framework versions

- Transformers 4.45.1
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0