---
library_name: transformers
license: apache-2.0
base_model: Qwen/Qwen2-1.5B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_per_domain_balanced
  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_per_domain_balanced

This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1209
- Accuracy: 0.9540

## 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: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.5664        | 0.0203 | 100  | 0.2706          | 0.8890   |
| 0.2871        | 0.0406 | 200  | 0.2891          | 0.8871   |
| 0.2495        | 0.0608 | 300  | 0.2310          | 0.9026   |
| 0.2414        | 0.0811 | 400  | 0.1710          | 0.9290   |
| 0.1983        | 0.1014 | 500  | 0.1614          | 0.9332   |
| 0.198         | 0.1217 | 600  | 0.1482          | 0.9394   |
| 0.2112        | 0.1419 | 700  | 0.1545          | 0.9443   |
| 0.1791        | 0.1622 | 800  | 0.1303          | 0.9501   |
| 0.1707        | 0.1825 | 900  | 0.1822          | 0.9340   |
| 0.1663        | 0.2028 | 1000 | 0.1297          | 0.9511   |
| 0.1657        | 0.2230 | 1100 | 0.1433          | 0.9492   |
| 0.1467        | 0.2433 | 1200 | 0.1107          | 0.9590   |
| 0.1519        | 0.2636 | 1300 | 0.1250          | 0.9548   |
| 0.1474        | 0.2839 | 1400 | 0.1045          | 0.9613   |
| 0.1509        | 0.3041 | 1500 | 0.1180          | 0.9593   |
| 0.147         | 0.3244 | 1600 | 0.1076          | 0.9588   |
| 0.1308        | 0.3447 | 1700 | 0.1209          | 0.9540   |


### Framework versions

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