---
license: llama3.1
base_model: NousResearch/Meta-Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
model-index:
- name: Llama-3.1-8B-Instruct-EI1-120K-fix-32gpus
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# Llama-3.1-8B-Instruct-EI1-120K-fix-32gpus

This model is a fine-tuned version of [NousResearch/Meta-Llama-3.1-8B-Instruct](https://huggingface.co/NousResearch/Meta-Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4036

## 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: 6e-06
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- total_train_batch_size: 64
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.95) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.2924 | 100  | 0.5279          |
| No log        | 0.5848 | 200  | 0.4631          |
| No log        | 0.8772 | 300  | 0.4304          |
| No log        | 1.1696 | 400  | 0.4153          |
| 0.4771        | 1.4620 | 500  | 0.4072          |
| 0.4771        | 1.7544 | 600  | 0.4036          |


### Framework versions

- Transformers 4.43.4
- Pytorch 2.4.0+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1