---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C020_random_sample_llama3-8b-base_pretrain_20240505_135320
  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. -->

# C020_random_sample_llama3-8b-base_pretrain_20240505_135320

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 C020_random_sample_data dataset.
It achieves the following results on the evaluation set:
- Loss: 1.9418

## 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: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- total_train_batch_size: 32
- total_eval_batch_size: 64
- 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 |
|:-------------:|:------:|:----:|:---------------:|
| 1.9087        | 0.4032 | 200  | 1.9717          |
| 1.8752        | 0.8065 | 400  | 1.9418          |
| 1.6383        | 1.2097 | 600  | 1.9440          |
| 1.7073        | 1.6129 | 800  | 1.9435          |
| 1.6699        | 2.0161 | 1000 | 1.9428          |
| 1.7212        | 2.4194 | 1200 | 1.9445          |
| 1.7346        | 2.8226 | 1400 | 1.9443          |
| 1.7028        | 3.2258 | 1600 | 1.9448          |
| 1.7383        | 3.6290 | 1800 | 1.9450          |


### Framework versions

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