---
license: other
base_model: meta-llama/Meta-Llama-3-8B
tags:
- llama-factory
- full
- generated_from_trainer
model-index:
- name: C013_llama3-8b-base_instruct_20240428_005832
  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_llama3-8b-base_instruct_20240428_005832

This model is a fine-tuned version of [./output/training_results/C013_llama3-8b-base_pretrain_20240428_005832/](https://huggingface.co/./output/training_results/C013_llama3-8b-base_pretrain_20240428_005832/) on the instructions_curated dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8123

## 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 |
|:-------------:|:------:|:----:|:---------------:|
| 0.9805        | 0.0208 | 1    | 0.9737          |
| 0.9446        | 0.1042 | 5    | 0.9455          |
| 0.8481        | 0.2083 | 10   | 0.8154          |
| 0.7794        | 0.3125 | 15   | 0.8123          |
| 0.7798        | 0.4167 | 20   | 0.8411          |
| 0.8576        | 0.5208 | 25   | 0.8676          |
| 0.8852        | 0.625  | 30   | 0.8673          |
| 0.8529        | 0.7292 | 35   | 0.8561          |
| 0.8224        | 0.8333 | 40   | 0.8470          |
| 0.8536        | 0.9375 | 45   | 0.8378          |
| 0.662         | 1.0417 | 50   | 0.8294          |
| 0.437         | 1.1458 | 55   | 0.8531          |
| 0.4402        | 1.25   | 60   | 0.8569          |
| 0.4244        | 1.3542 | 65   | 0.8569          |
| 0.4495        | 1.4583 | 70   | 0.8547          |
| 0.4689        | 1.5625 | 75   | 0.8494          |
| 0.4309        | 1.6667 | 80   | 0.8461          |
| 0.4299        | 1.7708 | 85   | 0.8446          |
| 0.4461        | 1.875  | 90   | 0.8440          |
| 0.4474        | 1.9792 | 95   | 0.8439          |
| 0.3614        | 2.0833 | 100  | 0.8445          |
| 0.3861        | 2.1875 | 105  | 0.8457          |
| 0.3829        | 2.2917 | 110  | 0.8473          |
| 0.3764        | 2.3958 | 115  | 0.8488          |
| 0.3655        | 2.5    | 120  | 0.8500          |
| 0.4243        | 2.6042 | 125  | 0.8511          |
| 0.3884        | 2.7083 | 130  | 0.8520          |
| 0.3634        | 2.8125 | 135  | 0.8528          |
| 0.3846        | 2.9167 | 140  | 0.8537          |
| 0.3872        | 3.0208 | 145  | 0.8547          |
| 0.3869        | 3.125  | 150  | 0.8558          |
| 0.3876        | 3.2292 | 155  | 0.8566          |
| 0.3844        | 3.3333 | 160  | 0.8573          |
| 0.3535        | 3.4375 | 165  | 0.8579          |
| 0.3488        | 3.5417 | 170  | 0.8588          |
| 0.3464        | 3.6458 | 175  | 0.8598          |
| 0.361         | 3.75   | 180  | 0.8607          |
| 0.3674        | 3.8542 | 185  | 0.8612          |
| 0.3988        | 3.9583 | 190  | 0.8612          |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1