---
license: llama3
library_name: peft
tags:
- trl
- sft
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
datasets:
- generator
model-index:
- name: cls_alldata_llama3_v1
  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. -->

# cls_alldata_llama3_v1

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B-Instruct](https://huggingface.co/meta-llama/Meta-Llama-3-8B-Instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4523

## 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: 0.0002
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: constant
- lr_scheduler_warmup_ratio: 0.03
- num_epochs: 2
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6921        | 0.0582 | 20   | 0.6831          |
| 0.5975        | 0.1164 | 40   | 0.6416          |
| 0.6107        | 0.1747 | 60   | 0.6082          |
| 0.5609        | 0.2329 | 80   | 0.5883          |
| 0.5857        | 0.2911 | 100  | 0.5761          |
| 0.5386        | 0.3493 | 120  | 0.5660          |
| 0.5176        | 0.4076 | 140  | 0.5529          |
| 0.5317        | 0.4658 | 160  | 0.5379          |
| 0.5244        | 0.5240 | 180  | 0.5292          |
| 0.5218        | 0.5822 | 200  | 0.5234          |
| 0.5003        | 0.6405 | 220  | 0.5207          |
| 0.5024        | 0.6987 | 240  | 0.5096          |
| 0.4913        | 0.7569 | 260  | 0.5062          |
| 0.5174        | 0.8151 | 280  | 0.5003          |
| 0.4675        | 0.8734 | 300  | 0.4968          |
| 0.5137        | 0.9316 | 320  | 0.4903          |
| 0.4883        | 0.9898 | 340  | 0.4869          |
| 0.3616        | 1.0480 | 360  | 0.4935          |
| 0.3713        | 1.1063 | 380  | 0.4890          |
| 0.365         | 1.1645 | 400  | 0.4856          |
| 0.3732        | 1.2227 | 420  | 0.4838          |
| 0.3717        | 1.2809 | 440  | 0.4842          |
| 0.3657        | 1.3392 | 460  | 0.4811          |
| 0.3767        | 1.3974 | 480  | 0.4762          |
| 0.3859        | 1.4556 | 500  | 0.4763          |
| 0.3773        | 1.5138 | 520  | 0.4712          |
| 0.3615        | 1.5721 | 540  | 0.4671          |
| 0.3656        | 1.6303 | 560  | 0.4666          |
| 0.3497        | 1.6885 | 580  | 0.4658          |
| 0.3818        | 1.7467 | 600  | 0.4621          |
| 0.3759        | 1.8049 | 620  | 0.4626          |
| 0.3539        | 1.8632 | 640  | 0.4551          |
| 0.3985        | 1.9214 | 660  | 0.4525          |
| 0.3668        | 1.9796 | 680  | 0.4523          |


### Framework versions

- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1