---
library_name: transformers
license: llama3.1
base_model: meta-llama/Meta-Llama-3.1-8B
tags:
- llama-factory
- generated_from_trainer
model-index:
- name: orca-agentinstruct-1M-v1-cleaned
  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. -->

# orca-agentinstruct-1M-v1-cleaned

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B](https://huggingface.co/meta-llama/Meta-Llama-3.1-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4721

## 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: 5e-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 2
- total_train_batch_size: 512
- total_eval_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.1
- lr_scheduler_warmup_steps: 1738
- num_epochs: 3.0

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.4816        | 0.9994 | 908  | 0.4857          |
| 0.4296        | 2.0    | 1817 | 0.4724          |
| 0.3803        | 2.9983 | 2724 | 0.4721          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.3.0
- Datasets 2.21.0
- Tokenizers 0.20.3