QWEN_without_time

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QWEN_without_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: 0.3017

• Balanced Accuracy: 0.8957

• Accuracy: 0.8957

• Micro F1: 0.8957

• Macro F1: 0.8957

• Weighted F1: 0.8957

• Classification Report: precision recall f1-score support

       0       0.90      0.89      0.90       386
       1       0.89      0.90      0.90       381
  

  accuracy 0.90 767 macro avg 0.90 0.90 0.90 767 weighted avg 0.90 0.90 0.90 767

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

       0       0.88      0.87      0.87       386
       1       0.87      0.88      0.87       381

accuracy                           0.87       767

macro avg 0.87 0.87 0.87 767 weighted avg 0.87 0.87 0.87 767 | | 0.3341 | 2.0 | 768 | 0.4140 | 0.8624 | 0.8631 | 0.8631 | 0.8612 | 0.8613 | precision recall f1-score support

       0       0.80      0.97      0.88       386
       1       0.97      0.75      0.84       381

accuracy                           0.86       767

macro avg 0.88 0.86 0.86 767 weighted avg 0.88 0.86 0.86 767 | | 0.2934 | 3.0 | 1152 | 0.3017 | 0.8957 | 0.8957 | 0.8957 | 0.8957 | 0.8957 | precision recall f1-score support

       0       0.90      0.89      0.90       386
       1       0.89      0.90      0.90       381

accuracy                           0.90       767

macro avg 0.90 0.90 0.90 767 weighted avg 0.90 0.90 0.90 767 |

Framework versions

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