fahmiaziz/t5-medical-diagnosis

t5_medical_diagnostic_peft

This model is a fine-tuned version of t5-base on an unknown dataset. It achieves the following results on the evaluation set:

• Loss: 1.7468
• Rouge1: 0.4227
• Rouge2: 0.2234
• Rougel: 0.3594
• Rougelsum: 0.3595
• Gen Len: 17.5843

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: 0.001
• 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: 1
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.9974	0.2	500	1.7864	0.4167	0.221	0.3561	0.356	17.6092
1.9244	0.4	1000	1.7504	0.4166	0.2214	0.3577	0.3577	16.9937
1.9121	0.6	1500	1.7274	0.4209	0.2245	0.3593	0.3594	17.2876
1.8677	0.8	2000	1.7101	0.4253	0.2266	0.363	0.3631	17.5681
1.8927	1.0	2500	1.7468	0.4227	0.2234	0.3594	0.3595	17.5843

Framework versions

• Transformers 4.35.0.dev0
• Pytorch 2.1.0+cu118
• Datasets 2.14.6
• Tokenizers 0.14.1