---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C017_random_sample_llama3-8b-base_pretrain_20240504_182259
  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. -->

# C017_random_sample_llama3-8b-base_pretrain_20240504_182259

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 C017_random_sample_data dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4690

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 2.5442        | 0.2028 | 200  | 2.5552          |
| 2.5376        | 0.4057 | 400  | 2.5096          |
| 2.4487        | 0.6085 | 600  | 2.4831          |
| 2.5324        | 0.8114 | 800  | 2.4690          |
| 2.265         | 1.0142 | 1000 | 2.4733          |
| 2.3002        | 1.2170 | 1200 | 2.4736          |
| 2.29          | 1.4199 | 1400 | 2.4734          |
| 2.2566        | 1.6227 | 1600 | 2.4725          |
| 2.3052        | 1.8256 | 1800 | 2.4721          |
| 2.2702        | 2.0284 | 2000 | 2.4734          |
| 2.2411        | 2.2312 | 2200 | 2.4746          |
| 2.2413        | 2.4341 | 2400 | 2.4749          |
| 2.216         | 2.6369 | 2600 | 2.4749          |
| 2.2696        | 2.8398 | 2800 | 2.4747          |
| 2.2455        | 3.0426 | 3000 | 2.4752          |
| 2.216         | 3.2454 | 3200 | 2.4753          |
| 2.2348        | 3.4483 | 3400 | 2.4757          |
| 2.238         | 3.6511 | 3600 | 2.4753          |
| 2.2349        | 3.8540 | 3800 | 2.4752          |


### Framework versions

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