medical_diagnostic_summarizer

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

• Loss: 1.8670
• Rouge1: 0.4177
• Rouge2: 0.2184
• Rougel: 0.3563
• Rougelsum: 0.3564
• Gen Len: 17.6943

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: 3

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.1658	1.0	2500	1.9703	0.411	0.2134	0.3502	0.3502	17.6057
1.9441	2.0	5000	1.8830	0.4155	0.2172	0.355	0.3551	17.6832
1.7621	3.0	7500	1.8670	0.4177	0.2184	0.3563	0.3564	17.6943

Framework versions

• Transformers 4.34.1
• Pytorch 2.1.0+cu118
• Datasets 2.14.5
• Tokenizers 0.14.1