---
library_name: transformers
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: openmathinstruct2-llama-3.1-8B-Instruct-lr5-ep2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# openmathinstruct2-llama-3.1-8B-Instruct-lr5-ep2

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on the openmathinstruct2_cot_20k_train dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7634

## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8177        | 0.4808 | 500  | 0.7823          |
| 0.7708        | 0.9615 | 1000 | 0.7572          |
| 0.5513        | 1.4423 | 1500 | 0.7693          |
| 0.5059        | 1.9231 | 2000 | 0.7637          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.3.0+cu121
- Datasets 2.21.0
- Tokenizers 0.20.1