SOMD-scibert-stage1-v1

This model is a fine-tuned version of allenai/scibert_scivocab_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: 20

Training results

Training Loss	Epoch	Step	Validation Loss	F1
No log	1.0	1243	0.0019	0.9022
No log	2.0	2486	0.0007	0.9530
No log	3.0	3729	0.0006	0.9749
No log	4.0	4972	0.0006	0.9697
No log	5.0	6215	0.0003	0.9830
No log	6.0	7458	0.0007	0.9759
No log	7.0	8701	0.0003	0.9867
No log	8.0	9944	0.0002	0.9900
No log	9.0	11187	0.0001	0.9932
No log	10.0	12430	0.0002	0.9951
No log	11.0	13673	0.0001	0.9932
No log	12.0	14916	0.0000	0.9978
No log	13.0	16159	0.0000	0.9977
No log	14.0	17402	0.0000	0.9985
No log	15.0	18645	0.0000	0.9994
No log	16.0	19888	0.0000	0.9992
No log	17.0	21131	0.0000	0.9997
No log	18.0	22374	0.0000	1.0
No log	19.0	23617	0.0000	1.0
No log	20.0	24860	0.0000	1.0

Framework versions

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