---
base_model: Qwen/Qwen2.5-0.5B-Instruct
datasets:
- generator
library_name: peft
license: apache-2.0
tags:
- trl
- sft
- generated_from_trainer
model-index:
- name: trained_model
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# trained_model

This model is a fine-tuned version of [Qwen/Qwen2.5-0.5B-Instruct](https://huggingface.co/Qwen/Qwen2.5-0.5B-Instruct) on the generator dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5432
- Bertscore Precision: 0.9305
- Bertscore Recall: 0.9338
- Bertscore F1: 0.9321

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 5

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:------:|:----:|:---------------:|:-------------------:|:----------------:|:------------:|
| No log        | 0.9664 | 18   | 1.1003          | 0.8802              | 0.8897           | 0.8849       |
| 1.7123        | 1.9866 | 37   | 0.6787          | 0.9207              | 0.9228           | 0.9218       |
| 1.7123        | 2.9530 | 55   | 0.5895          | 0.9300              | 0.9330           | 0.9315       |
| 0.5828        | 3.9732 | 74   | 0.5516          | 0.9330              | 0.9355           | 0.9342       |
| 0.4501        | 4.8322 | 90   | 0.5432          | 0.9305              | 0.9338           | 0.9321       |


### Framework versions

- PEFT 0.13.0
- Transformers 4.45.1
- Pytorch 2.5.1+cpu
- Datasets 3.0.1
- Tokenizers 0.20.0