---
library_name: peft
license: llama3.1
base_model: meta-llama/Llama-3.1-8B-Instruct
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: llama-7b-sst-5
  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. -->

# llama-7b-sst-5

This model is a fine-tuned version of [meta-llama/Llama-3.1-8B-Instruct](https://huggingface.co/meta-llama/Llama-3.1-8B-Instruct) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3537
- Accuracy: 0.4387
- Precision: 0.4393
- Recall: 0.4264
- F1: 0.4300

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:------:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| No log        | 1.4944 | 100  | 1.7838          | 0.3397   | 0.3352    | 0.3371 | 0.3321 |
| No log        | 2.9888 | 200  | 1.5155          | 0.3960   | 0.3916    | 0.3767 | 0.3782 |
| No log        | 4.4794 | 300  | 1.4366          | 0.4169   | 0.4313    | 0.4031 | 0.4106 |
| No log        | 5.9738 | 400  | 1.3832          | 0.4287   | 0.4224    | 0.4207 | 0.4198 |
| 5.8948        | 7.4644 | 500  | 1.3675          | 0.4369   | 0.4489    | 0.4266 | 0.4345 |
| 5.8948        | 8.9588 | 600  | 1.3537          | 0.4387   | 0.4393    | 0.4264 | 0.4300 |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.1
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0