cosent-similarity-text2vec

This model is a fine-tuned version of shibing624/text2vec-base-chinese on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.1408
• Accuracy: 0.9605
• F1: 0.9670
• Precision: 0.9778
• Recall: 0.9565

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: 2e-05
• train_batch_size: 32
• eval_batch_size: 32
• 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	Accuracy	F1	Precision	Recall
No log	1.0	22	0.2330	0.9211	0.9318	0.9762	0.8913
No log	2.0	44	0.2088	0.9342	0.9438	0.9767	0.9130
No log	3.0	66	0.1484	0.9605	0.9670	0.9778	0.9565
No log	4.0	88	0.1370	0.9605	0.9670	0.9778	0.9565
No log	5.0	110	0.1408	0.9605	0.9670	0.9778	0.9565

Framework versions

• Transformers 4.37.2
• Pytorch 2.1.2
• Datasets 2.18.0
• Tokenizers 0.15.1