SOMD-train-bert-v3

This model is a fine-tuned version of bert-base-cased on the None dataset. It achieves the following results on the evaluation set:

• Loss: 0.0000
• F1: 1.0

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: 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: 10

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	1243	0.0048	0.7214
No log	2.0	2486	0.0024	0.8299
No log	3.0	3729	0.0011	0.9137
No log	4.0	4972	0.0006	0.9494
No log	5.0	6215	0.0002	0.9820
No log	6.0	7458	0.0001	0.9888
No log	7.0	8701	0.0003	0.9839
No log	8.0	9944	0.0001	0.9960
No log	9.0	11187	0.0000	0.9995
No log	10.0	12430	0.0000	1.0

Framework versions

• Transformers 4.37.0
• Pytorch 2.1.2
• Datasets 2.1.0
• Tokenizers 0.15.1