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

This model is a fine-tuned version of [Qwen/Qwen2-1.5B](https://huggingface.co/Qwen/Qwen2-1.5B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1573
- Accuracy: 0.9597

## 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: 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: 3

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| 0.7991        | 0.0289 | 100  | 0.3764          | 0.8394   |
| 0.6153        | 0.0578 | 200  | 0.3492          | 0.8602   |
| 0.3929        | 0.0867 | 300  | 0.5004          | 0.8501   |
| 0.7981        | 0.1156 | 400  | 0.3459          | 0.8677   |
| 0.5853        | 0.1445 | 500  | 0.3124          | 0.8787   |
| 0.3284        | 0.1734 | 600  | 0.2438          | 0.9308   |
| 0.3591        | 0.2023 | 700  | 0.2842          | 0.9041   |
| 0.332         | 0.2311 | 800  | 0.3904          | 0.9038   |
| 0.3424        | 0.2600 | 900  | 0.2234          | 0.9402   |
| 0.2609        | 0.2889 | 1000 | 0.2586          | 0.9249   |
| 0.3036        | 0.3178 | 1100 | 0.2775          | 0.9204   |
| 0.2429        | 0.3467 | 1200 | 0.1521          | 0.9441   |
| 0.2495        | 0.3756 | 1300 | 0.2326          | 0.9512   |
| 0.2486        | 0.4045 | 1400 | 0.2712          | 0.9467   |
| 0.1711        | 0.4334 | 1500 | 0.1573          | 0.9597   |


### Framework versions

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