README.md

metadata

license: mit
base_model: BAAI/bge-base-en-v1.5
tags:
  - generated_from_trainer
model-index:
  - name: SECTOR-multilabel-bge
    results: []

SECTOR-multilabel-bge

This model is a fine-tuned version of BAAI/bge-base-en-v1.5 on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.6114
• Precision-micro: 0.6428
• Precision-samples: 0.7488
• Precision-weighted: 0.6519
• Recall-micro: 0.7855
• Recall-samples: 0.8627
• Recall-weighted: 0.7855
• F1-micro: 0.7071
• F1-samples: 0.7638
• F1-weighted: 0.7109

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: 7.04e-05
• train_batch_size: 16
• eval_batch_size: 16
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: cosine
• lr_scheduler_warmup_steps: 300
• num_epochs: 7

Training results

Training Loss	Epoch	Step	Validation Loss	Precision-micro	Precision-samples	Precision-weighted	Recall-micro	Recall-samples	Recall-weighted	F1-micro	F1-samples	F1-weighted
0.7077	1.0	633	0.5490	0.4226	0.5465	0.4954	0.8211	0.8908	0.8211	0.5580	0.6243	0.5977
0.4546	2.0	1266	0.5009	0.4899	0.6127	0.5202	0.8438	0.9023	0.8438	0.6199	0.6822	0.6366
0.3105	3.0	1899	0.4947	0.5005	0.6593	0.5317	0.8508	0.8970	0.8508	0.6303	0.7125	0.6474
0.2044	4.0	2532	0.5430	0.5757	0.7044	0.5970	0.8106	0.8801	0.8106	0.6733	0.7379	0.6834
0.1314	5.0	3165	0.5633	0.6132	0.7385	0.6271	0.8065	0.8772	0.8065	0.6967	0.7606	0.7032
0.0892	6.0	3798	0.6073	0.6425	0.7499	0.6545	0.7844	0.8610	0.7844	0.7064	0.7634	0.7113
0.0721	7.0	4431	0.6114	0.6428	0.7488	0.6519	0.7855	0.8627	0.7855	0.7071	0.7638	0.7109

Framework versions

• Transformers 4.38.1
• Pytorch 2.1.0+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2