---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C016_random_sample_llama3-8b-base_pretrain_20240504_181744
  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. -->

# C016_random_sample_llama3-8b-base_pretrain_20240504_181744

This model is a fine-tuned version of [/data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base](https://huggingface.co//data/pro-align/progressalign/shared_storage/downloaded_models/llama3-8b-base) on the C016_random_sample_data dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4196

## 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: 1.5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 64
- total_eval_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 20
- num_epochs: 4.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 2.5472        | 0.1947 | 200  | 2.5262          |
| 2.4431        | 0.3895 | 400  | 2.4733          |
| 2.4163        | 0.5842 | 600  | 2.4443          |
| 2.4462        | 0.7790 | 800  | 2.4281          |
| 2.4353        | 0.9737 | 1000 | 2.4196          |
| 2.2111        | 1.1685 | 1200 | 2.4290          |
| 2.2503        | 1.3632 | 1400 | 2.4281          |
| 2.258         | 1.5579 | 1600 | 2.4271          |
| 2.254         | 1.7527 | 1800 | 2.4266          |
| 2.2508        | 1.9474 | 2000 | 2.4266          |
| 2.2112        | 2.1422 | 2200 | 2.4287          |
| 2.2063        | 2.3369 | 2400 | 2.4293          |
| 2.2544        | 2.5316 | 2600 | 2.4291          |
| 2.2024        | 2.7264 | 2800 | 2.4289          |
| 2.2074        | 2.9211 | 3000 | 2.4288          |
| 2.2268        | 3.1159 | 3200 | 2.4297          |
| 2.1556        | 3.3106 | 3400 | 2.4294          |
| 2.1953        | 3.5054 | 3600 | 2.4296          |
| 2.2002        | 3.7001 | 3800 | 2.4294          |
| 2.2437        | 3.8948 | 4000 | 2.4291          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0
- Datasets 2.19.0
- Tokenizers 0.19.1