---
base_model: meta-llama/Llama-2-7b-hf
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hubbub-topics
  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-topics

This model is a fine-tuned version of [meta-llama/Llama-2-7b-hf](https://huggingface.co/meta-llama/Llama-2-7b-hf) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5901
- Accuracy: 0.8152
- Precision: 0.8134
- Recall: 0.8152
- F1: 0.8079

## Model description

Hubbub Categories/Topics fine-tuned model

## 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


### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
| 1.209         | 1.0   | 1406 | 1.0149          | 0.6644   | 0.6512    | 0.6644 | 0.6460 |
| 1.0161        | 2.0   | 2812 | 0.8027          | 0.7444   | 0.7414    | 0.7444 | 0.7327 |
| 0.7695        | 3.0   | 4218 | 0.5901          | 0.8152   | 0.8134    | 0.8152 | 0.8079 |


### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3