metadata

license: apache-2.0
library_name: peft
tags:
  - generated_from_trainer
base_model: Qwen/Qwen2-7B
metrics:
  - accuracy
model-index:
  - name: QWEN_with_time
    results: []

QWEN_with_time

This model is a fine-tuned version of Qwen/Qwen2-7B on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3495
Balanced Accuracy: 0.8801
Accuracy: 0.8801
Micro F1: 0.8801
Macro F1: 0.8800
Weighted F1: 0.8800
Classification Report: precision recall f1-score support
```
     0       0.89      0.87      0.88       386
     1       0.87      0.89      0.88       381
```
accuracy 0.88 767 macro avg 0.88 0.88 0.88 767

weighted avg 0.88 0.88 0.88 767

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: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Balanced Accuracy	Accuracy	Micro F1	Macro F1	Weighted F1	Classification Report
0.6244	1.0	384	0.4657	0.8336	0.8331	0.8331	0.8323	0.8322	precision recall f1-score support

       0       0.89      0.76      0.82       386
       1       0.79      0.91      0.84       381

accuracy                           0.83       767

macro avg 0.84 0.83 0.83 767 weighted avg 0.84 0.83 0.83 767 | | 0.3513 | 2.0 | 768 | 0.4065 | 0.8639 | 0.8644 | 0.8644 | 0.8634 | 0.8635 | precision recall f1-score support

       0       0.82      0.94      0.88       386
       1       0.93      0.78      0.85       381

accuracy                           0.86       767

macro avg 0.87 0.86 0.86 767 weighted avg 0.87 0.86 0.86 767 | | 0.2858 | 3.0 | 1152 | 0.3495 | 0.8801 | 0.8801 | 0.8801 | 0.8800 | 0.8800 | precision recall f1-score support

       0       0.89      0.87      0.88       386
       1       0.87      0.89      0.88       381

accuracy                           0.88       767

macro avg 0.88 0.88 0.88 767 weighted avg 0.88 0.88 0.88 767 |

Framework versions

PEFT 0.11.1
Transformers 4.41.2
Pytorch 2.3.0+cu121
Datasets 2.19.1
Tokenizers 0.19.1