---
license: other
base_model: Qwen/Qwen1.5-1.8B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: Qwen1.5_1.8B_twitter
  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. -->

# Qwen1.5_1.8B_twitter

This model is a fine-tuned version of [Qwen/Qwen1.5-1.8B](https://huggingface.co/Qwen/Qwen1.5-1.8B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5039
- Accuracy: 0.7776
- F1 Macro: 0.7420
- F1 Micro: 0.7776

## 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-06
- 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 0.6585        | 0.18  | 50   | 0.6435          | 0.7123   | 0.5811   | 0.7123   |
| 0.6396        | 0.37  | 100  | 0.6016          | 0.7298   | 0.6998   | 0.7298   |
| 0.5108        | 0.55  | 150  | 0.5227          | 0.7528   | 0.6963   | 0.7528   |
| 0.5065        | 0.74  | 200  | 0.5503          | 0.7417   | 0.6347   | 0.7417   |
| 0.4883        | 0.92  | 250  | 0.5039          | 0.7776   | 0.7420   | 0.7776   |
| 0.3296        | 1.1   | 300  | 0.5250          | 0.7730   | 0.7307   | 0.7730   |
| 0.322         | 1.29  | 350  | 0.5510          | 0.7721   | 0.7423   | 0.7721   |
| 0.3287        | 1.47  | 400  | 0.5392          | 0.7583   | 0.6932   | 0.7583   |
| 0.3097        | 1.65  | 450  | 0.5631          | 0.7629   | 0.7223   | 0.7629   |
| 0.3397        | 1.84  | 500  | 0.5669          | 0.7675   | 0.7334   | 0.7675   |
| 0.2618        | 2.02  | 550  | 0.5891          | 0.75     | 0.6870   | 0.75     |
| 0.1745        | 2.21  | 600  | 0.6400          | 0.7583   | 0.7123   | 0.7583   |
| 0.1572        | 2.39  | 650  | 0.6694          | 0.7518   | 0.6967   | 0.7518   |
| 0.1804        | 2.57  | 700  | 0.6870          | 0.7610   | 0.7173   | 0.7610   |
| 0.1817        | 2.76  | 750  | 0.6656          | 0.7537   | 0.7045   | 0.7537   |
| 0.1984        | 2.94  | 800  | 0.6783          | 0.7518   | 0.6949   | 0.7518   |


### Framework versions

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