Symptoms_to_Diagnosis_SonatafyAI_BERT_v1

This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 0.6203
• Accuracy: 0.9198

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: 16
• eval_batch_size: 16
• 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	Accuracy
No log	1.0	54	2.7261	0.2123
No log	2.0	108	2.2144	0.5283
No log	3.0	162	1.7385	0.6698
No log	4.0	216	1.3686	0.7925
No log	5.0	270	1.1194	0.8302
No log	6.0	324	0.9123	0.8632
No log	7.0	378	0.7822	0.9009
No log	8.0	432	0.6871	0.9009
No log	9.0	486	0.6415	0.9104
1.4504	10.0	540	0.6203	0.9198

Framework versions

• Transformers 4.40.1
• Pytorch 2.2.1+cu121
• Datasets 2.19.1
• Tokenizers 0.19.1