lbl-file1-fold2

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

• Loss: 1.2445
• Accuracy: 0.5872
• F1: 0.5800
• Precision: 0.5849
• Recall: 0.5872
• Accuracy Label Label 0: 0.8036
• Accuracy Label Label 1: 0.5837
• Accuracy Label Label 2: 0.5129
• Accuracy Label Label 3: 0.7791
• Accuracy Label Label 4: 0.6561
• Accuracy Label Label 5: 0.4428
• Accuracy Label Label 6: 0.7478
• Accuracy Label Label 7: 0.2723
• Accuracy Label Label 8: 0.6075
• Accuracy Label Label 9: 0.4333

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
1.325	0.64	100	1.2494	0.5848	0.5763	0.5832	0.5848	0.8071	0.5918	0.5216	0.7871	0.6522	0.4096	0.7478	0.2681	0.6	0.4333

Framework versions

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