---
license: llama3
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
- precision
- recall
model-index:
- name: llama3-8B_less_data_for_fact_update
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# llama3-8B_less_data_for_fact_update

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co./meta-llama/Meta-Llama-3-8B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7586
- Accuracy: 0.7733
- Precision: 0.8015
- Recall: 0.7267
- F1 score: 0.7622

## 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: 0.0001
- train_batch_size: 8
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
| 0.8492        | 0.5   | 200  | 0.8538          | 0.65     | 0.6923    | 0.54   | 0.6067   |
| 0.7574        | 1.0   | 400  | 0.6427          | 0.7267   | 0.8036    | 0.6    | 0.6870   |
| 0.5003        | 1.5   | 600  | 0.5917          | 0.73     | 0.7066    | 0.7867 | 0.7445   |
| 0.4629        | 2.0   | 800  | 0.6470          | 0.7567   | 0.8235    | 0.6533 | 0.7286   |
| 0.3114        | 2.5   | 1000 | 0.6980          | 0.6967   | 0.7438    | 0.6    | 0.6642   |
| 0.3031        | 3.0   | 1200 | 0.6128          | 0.7567   | 0.8130    | 0.6667 | 0.7326   |
| 0.1783        | 3.5   | 1400 | 0.7288          | 0.7667   | 0.8175    | 0.6867 | 0.7464   |
| 0.1737        | 4.0   | 1600 | 0.7242          | 0.7533   | 0.7969    | 0.68   | 0.7338   |
| 0.0924        | 4.5   | 1800 | 0.7214          | 0.7733   | 0.7808    | 0.76   | 0.7703   |
| 0.0669        | 5.0   | 2000 | 0.7586          | 0.7733   | 0.8015    | 0.7267 | 0.7622   |


### Framework versions

- PEFT 0.11.1
- Transformers 4.44.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1