mamba2_130m_multi_label_classification

This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.1412
• Flat Accuracy: 0.9617
• Accuracy: 0.7177
• Precision: 0.8407
• Recall: 0.8833
• F1 Score: 0.8615

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: 5e-05
• train_batch_size: 12
• eval_batch_size: 4
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss	Flat Accuracy	Accuracy	Precision	Recall	F1 Score
0.1343	1.0	1667	0.1075	0.9621	0.7243	0.8606	0.8579	0.8592
0.0783	2.0	3334	0.1110	0.9610	0.7129	0.8342	0.8874	0.8600
0.0233	3.0	5001	0.1305	0.9594	0.7031	0.8263	0.8854	0.8548
0.0055	4.0	6668	0.1398	0.9605	0.7072	0.8300	0.8895	0.8588
0.0022	5.0	8335	0.1412	0.9617	0.7177	0.8407	0.8833	0.8615

Framework versions

• Transformers 4.44.2
• Pytorch 2.1.1+cu118
• Datasets 3.1.0
• Tokenizers 0.19.1