---
base_model: meta-llama/Meta-Llama-3.1-8B-Instruct
library_name: peft
license: llama3.1
tags:
- trl
- sft
- generated_from_trainer
- text-classification
model-index:
- name: outputs
  results: []
---

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

This model is a fine-tuned version of [meta-llama/Meta-Llama-3.1-8B-Instruct](https://huggingface.co./meta-llama/Meta-Llama-3.1-8B-Instruct) and is intended for text classification tasks. It has been trained to classify text based on the provided labels in the training dataset.

## Model description

More information needed

## Intended uses & limitations

This model is intended for text classification tasks such as sentiment analysis, spam detection, or other binary/multiclass classification problems.

**Limitations**:
- The model might not perform well on tasks it has not been explicitly trained for.
- The performance may vary depending on the domain and the quality of the input data.

## 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: 2
- eval_batch_size: 8
- seed: 3407
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 10
- num_epochs: 1

### Training results



### Framework versions

- PEFT 0.12.0
- Transformers 4.43.3
- Pytorch 2.4.0+cu124
- Datasets 2.20.0
- Tokenizers 0.19.1