---
license: mit
base_model: roberta-base
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: Llama3-q4_k_m
  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-q4_k_m

This model is a fine-tuned version of [roberta-base](https://huggingface.co/roberta-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0938
- Accuracy: 0.9825
- F1: 0.9827

## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
| 0.3823        | 1.0   | 129  | 0.1932          | 0.9532   | 0.9535 |
| 0.1585        | 2.0   | 258  | 0.3872          | 0.8977   | 0.9057 |
| 0.3048        | 3.0   | 387  | 0.1816          | 0.9474   | 0.9477 |
| 0.2353        | 4.0   | 516  | 0.1817          | 0.9591   | 0.9605 |
| 0.2928        | 5.0   | 645  | 0.2058          | 0.9503   | 0.9524 |
| 0.2452        | 6.0   | 774  | 0.1246          | 0.9737   | 0.9742 |
| 0.348         | 7.0   | 903  | 0.0932          | 0.9825   | 0.9827 |
| 0.1316        | 8.0   | 1032 | 0.0938          | 0.9825   | 0.9827 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1