lbl-file0-fold3

This model was trained from scratch on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0791
• Accuracy: 0.978
• F1: 0.9780
• Precision: 0.9781
• Recall: 0.978
• Accuracy Label Label 0: 0.9960
• Accuracy Label Label 1: 0.9878
• Accuracy Label Label 2: 0.9810
• Accuracy Label Label 3: 0.9916
• Accuracy Label Label 4: 0.9837
• Accuracy Label Label 5: 0.9873
• Accuracy Label Label 6: 0.9698
• Accuracy Label Label 7: 0.9675
• Accuracy Label Label 8: 0.964
• Accuracy Label Label 9: 0.9538

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: 32
• eval_batch_size: 32
• seed: 42
• gradient_accumulation_steps: 2
• total_train_batch_size: 64
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_ratio: 0.1
• num_epochs: 1

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy	F1	Precision	Recall	Accuracy Label Label 0	Accuracy Label Label 1	Accuracy Label Label 2	Accuracy Label Label 3	Accuracy Label Label 4	Accuracy Label Label 5	Accuracy Label Label 6	Accuracy Label Label 7	Accuracy Label Label 8	Accuracy Label Label 9
No log	0.8	125	0.0857	0.9748	0.9748	0.9750	0.9748	0.9677	0.9837	0.9658	0.9874	0.9675	0.9958	0.9736	0.9715	0.98	0.9577

Framework versions

• Transformers 4.30.2
• Pytorch 2.5.1+cu124
• Datasets 3.2.0
• Tokenizers 0.13.3