---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: Qwen/Qwen1.5-7B
metrics:
- accuracy
model-index:
- name: twitter_disaster
  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. -->

# twitter_disaster

This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4902
- Accuracy: 0.7767
- F1 Macro: 0.7451
- F1 Micro: 0.7767

## 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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.8422        | 0.18  | 50   | 0.6453          | 0.7178   | 0.6372   | 0.7178   |
| 0.6082        | 0.37  | 100  | 0.5489          | 0.7472   | 0.7123   | 0.7472   |
| 0.4305        | 0.55  | 150  | 0.5572          | 0.7252   | 0.5777   | 0.7252   |
| 0.5021        | 0.74  | 200  | 0.5000          | 0.7721   | 0.7437   | 0.7721   |
| 0.4715        | 0.92  | 250  | 0.4902          | 0.7767   | 0.7451   | 0.7767   |
| 0.3937        | 1.1   | 300  | 0.5194          | 0.7601   | 0.7018   | 0.7601   |
| 0.4219        | 1.29  | 350  | 0.5228          | 0.7665   | 0.7228   | 0.7665   |
| 0.4315        | 1.47  | 400  | 0.5791          | 0.7555   | 0.6901   | 0.7555   |
| 0.4134        | 1.65  | 450  | 0.6182          | 0.7390   | 0.7196   | 0.7390   |
| 0.4173        | 1.84  | 500  | 0.5454          | 0.7638   | 0.7116   | 0.7638   |
| 0.3278        | 2.02  | 550  | 0.5477          | 0.7721   | 0.7219   | 0.7721   |
| 0.2641        | 2.21  | 600  | 0.6011          | 0.7528   | 0.7152   | 0.7528   |
| 0.2256        | 2.39  | 650  | 0.6485          | 0.7601   | 0.6962   | 0.7601   |
| 0.2544        | 2.57  | 700  | 0.6459          | 0.7629   | 0.7165   | 0.7629   |
| 0.2839        | 2.76  | 750  | 0.5922          | 0.7656   | 0.7253   | 0.7656   |
| 0.2634        | 2.94  | 800  | 0.6312          | 0.7638   | 0.7076   | 0.7638   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2