---
license: other
base_model: meta-llama/Meta-Llama-3-70B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C013_Meta-Llama-3-70B_pretrain_20240508_200642
  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. -->

# C013_Meta-Llama-3-70B_pretrain_20240508_200642

This model is a fine-tuned version of [/mnt/fl/models/llama3/Meta-Llama-3-70B](https://huggingface.co//mnt/fl/models/llama3/Meta-Llama-3-70B) on the C013_data dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7400

## 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: 3e-06
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 32
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_ratio: 0.075
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.8776        | 0.2090 | 7    | 0.7902          |
| 0.8473        | 0.4179 | 14   | 0.7703          |
| 0.8293        | 0.6269 | 21   | 0.7603          |
| 0.8173        | 0.8358 | 28   | 0.7481          |
| 0.7415        | 1.0448 | 35   | 0.7402          |
| 0.6794        | 1.2537 | 42   | 0.7419          |
| 0.6688        | 1.4627 | 49   | 0.7392          |
| 0.6498        | 1.6716 | 56   | 0.7367          |
| 0.6701        | 1.8806 | 63   | 0.7358          |
| 0.664         | 2.0896 | 70   | 0.7355          |
| 0.6447        | 2.2985 | 77   | 0.7361          |
| 0.6412        | 2.5075 | 84   | 0.7373          |
| 0.6458        | 2.7164 | 91   | 0.7383          |
| 0.6356        | 2.9254 | 98   | 0.7387          |
| 0.6398        | 3.1343 | 105  | 0.7387          |
| 0.6228        | 3.3433 | 112  | 0.7391          |
| 0.6139        | 3.5522 | 119  | 0.7395          |
| 0.591         | 3.7612 | 126  | 0.7398          |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.19.1