---
library_name: transformers
license: other
base_model: Qwen/Qwen1.5-32B
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: fine_tuned_per_domain_balanced_32B
  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_32B

This model is a fine-tuned version of [Qwen/Qwen1.5-32B](https://huggingface.co/Qwen/Qwen1.5-32B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7888
- Accuracy: 0.8908

## 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: 1
- eval_batch_size: 1
- 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 |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 1.8972        | 0.0029 | 500  | 1.5903          | 0.7475   |
| 2.0489        | 0.0057 | 1000 | 1.1390          | 0.8111   |
| 1.2974        | 0.0086 | 1500 | 1.2533          | 0.8057   |
| 1.3929        | 0.0114 | 2000 | 1.3143          | 0.8156   |
| 0.5961        | 0.0143 | 2500 | 1.0441          | 0.8451   |
| 0.4478        | 0.0172 | 3000 | 1.0491          | 0.8496   |
| 1.3262        | 0.0200 | 3500 | 1.0400          | 0.8478   |
| 0.9755        | 0.0229 | 4000 | 0.9457          | 0.8621   |
| 0.7849        | 0.0258 | 4500 | 0.8249          | 0.8684   |
| 0.7091        | 0.0286 | 5000 | 0.7580          | 0.8836   |
| 0.527         | 0.0315 | 5500 | 0.8654          | 0.8756   |
| 0.8061        | 0.0343 | 6000 | 0.8890          | 0.8782   |
| 0.1774        | 0.0372 | 6500 | 0.7888          | 0.8908   |


### Framework versions

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