---
license: other
library_name: peft
tags:
- generated_from_trainer
base_model: Qwen/Qwen1.5-7B
metrics:
- accuracy
model-index:
- name: amazon_attrprompt
  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. -->

# amazon_attrprompt

This model is a fine-tuned version of [Qwen/Qwen1.5-7B](https://huggingface.co/Qwen/Qwen1.5-7B) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4250
- Accuracy: 0.8709
- F1 Macro: 0.8541
- F1 Micro: 0.8709

## 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-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- total_train_batch_size: 32
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Macro | F1 Micro |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:--------:|:--------:|
| 1.6833        | 0.13  | 50   | 1.2279          | 0.6640   | 0.5879   | 0.6640   |
| 0.6531        | 0.26  | 100  | 0.6578          | 0.8155   | 0.7767   | 0.8155   |
| 0.6075        | 0.39  | 150  | 0.5935          | 0.8327   | 0.8113   | 0.8327   |
| 0.5646        | 0.53  | 200  | 0.5660          | 0.8379   | 0.8194   | 0.8379   |
| 0.6148        | 0.66  | 250  | 0.5318          | 0.8426   | 0.8319   | 0.8426   |
| 0.4047        | 0.79  | 300  | 0.4546          | 0.8650   | 0.8467   | 0.8650   |
| 0.568         | 0.92  | 350  | 0.4250          | 0.8709   | 0.8541   | 0.8709   |
| 0.2395        | 1.05  | 400  | 0.4570          | 0.8762   | 0.8611   | 0.8762   |
| 0.2213        | 1.18  | 450  | 0.4524          | 0.8775   | 0.8631   | 0.8775   |
| 0.1778        | 1.32  | 500  | 0.4649          | 0.8748   | 0.8508   | 0.8748   |
| 0.1738        | 1.45  | 550  | 0.4853          | 0.8794   | 0.8617   | 0.8794   |
| 0.2643        | 1.58  | 600  | 0.4302          | 0.8827   | 0.8676   | 0.8827   |
| 0.3357        | 1.71  | 650  | 0.4388          | 0.8827   | 0.8673   | 0.8827   |
| 0.3029        | 1.84  | 700  | 0.4431          | 0.8827   | 0.8656   | 0.8827   |
| 0.1809        | 1.97  | 750  | 0.4266          | 0.8900   | 0.8742   | 0.8900   |
| 0.0589        | 2.11  | 800  | 0.4499          | 0.8946   | 0.8815   | 0.8946   |
| 0.0531        | 2.24  | 850  | 0.4758          | 0.8920   | 0.8758   | 0.8920   |
| 0.0234        | 2.37  | 900  | 0.4788          | 0.8953   | 0.8804   | 0.8953   |
| 0.0145        | 2.5   | 950  | 0.4976          | 0.8939   | 0.8779   | 0.8939   |
| 0.058         | 2.63  | 1000 | 0.4967          | 0.8992   | 0.8816   | 0.8992   |
| 0.05          | 2.76  | 1050 | 0.5113          | 0.8933   | 0.8753   | 0.8933   |
| 0.0556        | 2.89  | 1100 | 0.5024          | 0.8966   | 0.8803   | 0.8966   |


### Framework versions

- PEFT 0.9.0
- Transformers 4.39.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2