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---
license: llama3
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B-Instruct
model-index:
- name: llama3-8b-instruct-journal-finetune
  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. -->

# llama3-8b-instruct-journal-finetune

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 None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.0299

## 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: 2.5e-05
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- training_steps: 500

### Training results

| Training Loss | Epoch   | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 2.9002        | 2.0833  | 25   | 1.8777          |
| 1.1645        | 4.1667  | 50   | 1.6214          |
| 0.4078        | 6.25    | 75   | 1.7856          |
| 0.2373        | 8.3333  | 100  | 1.8434          |
| 0.2209        | 10.4167 | 125  | 1.7767          |
| 0.1953        | 12.5    | 150  | 1.8293          |
| 0.1755        | 14.5833 | 175  | 1.7663          |
| 0.1893        | 16.6667 | 200  | 1.8726          |
| 0.1621        | 18.75   | 225  | 1.9366          |
| 0.1657        | 20.8333 | 250  | 1.9146          |
| 0.1593        | 22.9167 | 275  | 1.9225          |
| 0.156         | 25.0    | 300  | 1.9411          |
| 0.1549        | 27.0833 | 325  | 1.9504          |
| 0.1525        | 29.1667 | 350  | 1.9608          |
| 0.1511        | 31.25   | 375  | 1.9924          |
| 0.1494        | 33.3333 | 400  | 1.9878          |
| 0.1488        | 35.4167 | 425  | 2.0089          |
| 0.1479        | 37.5    | 450  | 2.0089          |
| 0.1448        | 39.5833 | 475  | 2.0233          |
| 0.1447        | 41.6667 | 500  | 2.0299          |


### Framework versions

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