---
library_name: transformers
license: other
base_model: Qwen/Qwen1.5-1.8B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_all_domains_1.5
  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. -->

# fine_tuned_all_domains_1.5

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: 0.2531
- Accuracy: 0.9460

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.4234        | 0.0126 | 500  | 0.3614          | 0.8957   |
| 0.2949        | 0.0252 | 1000 | 0.2974          | 0.9101   |
| 0.3592        | 0.0377 | 1500 | 0.2913          | 0.9137   |
| 0.3101        | 0.0503 | 2000 | 0.2877          | 0.9326   |
| 0.2923        | 0.0629 | 2500 | 0.2246          | 0.9290   |
| 0.2778        | 0.0755 | 3000 | 0.2472          | 0.9397   |
| 0.2556        | 0.0881 | 3500 | 0.2163          | 0.9487   |
| 0.2986        | 0.1006 | 4000 | 0.2156          | 0.9478   |
| 0.272         | 0.1132 | 4500 | 0.2387          | 0.9388   |
| 0.2363        | 0.1258 | 5000 | 0.4263          | 0.9326   |
| 0.221         | 0.1384 | 5500 | 0.2054          | 0.9505   |
| 0.2478        | 0.1510 | 6000 | 0.2851          | 0.9451   |
| 0.2451        | 0.1635 | 6500 | 0.2730          | 0.9442   |
| 0.1915        | 0.1761 | 7000 | 0.2531          | 0.9460   |


### Framework versions

- Transformers 4.49.0
- Pytorch 2.6.0+cu126
- Datasets 3.3.2
- Tokenizers 0.21.0