lbl-file1-fold3

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

• Loss: 1.2723
• Accuracy: 0.568
• F1: 0.5607
• Precision: 0.5645
• Recall: 0.568
• Accuracy Label Label 0: 0.8226
• Accuracy Label Label 1: 0.5813
• Accuracy Label Label 2: 0.4715
• Accuracy Label Label 3: 0.7741
• Accuracy Label Label 4: 0.6585
• Accuracy Label Label 5: 0.4262
• Accuracy Label Label 6: 0.6604
• Accuracy Label Label 7: 0.2358
• Accuracy Label Label 8: 0.636
• Accuracy Label Label 9: 0.4192

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: 1e-06
• 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
1.2768	0.64	100	1.2751	0.5684	0.5607	0.5648	0.5684	0.8266	0.5772	0.4677	0.7782	0.6585	0.4262	0.6604	0.2358	0.636	0.4231

Framework versions

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