---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: meta-llama/Meta-Llama-3-8B
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hubbub-sentiment_llama3
  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. -->

# hubbub-sentiment_llama3

This model is a fine-tuned version of [meta-llama/Meta-Llama-3-8B](https://huggingface.co/meta-llama/Meta-Llama-3-8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4586
- Accuracy: 0.8269
- Precision: 0.8234
- Recall: 0.8269
- F1: 0.8235

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 0.821         | 0.9998 | 1406 | 0.8073          | 0.6595   | 0.7055    | 0.6595 | 0.5621 |
| 0.7134        | 1.9996 | 2812 | 0.6063          | 0.7508   | 0.7422    | 0.7508 | 0.7427 |
| 0.5814        | 2.9995 | 4218 | 0.4586          | 0.8269   | 0.8234    | 0.8269 | 0.8235 |


### Framework versions

- PEFT 0.10.0
- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1