pi-medical-extractor-clinicalt5-lora – AI Model by tjarzu | AlphaNeural AI

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tjarzu/
pi-medical-extractor-clinicalt5-lora

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text2text-generation

avikalsingh/Clinical-T5-Base

text-generation-inference

endpoints_compatible

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pi-medical-extractor-clinicalt5-lora

This model is a fine-tuned version of avikalsingh/Clinical-T5-Base on the None dataset. It achieves the following results on the evaluation set:

Loss: 3.0244

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: cosine
lr_scheduler_warmup_steps: 0.05
num_epochs: 3

Training results

Training Loss	Epoch	Step	Validation Loss
2.4523	0.32	200	2.2601
1.3644	0.64	400	2.4665
1.0832	0.96	600	2.6644
0.9997	1.28	800	2.7890
0.9100	1.6	1000	2.9128
0.8851	1.92	1200	2.9407
0.8583	2.24	1400	2.9958
0.8518	2.56	1600	3.0368
0.8657	2.88	1800	3.0209
0.8513	3.0	1875	3.0244

Framework versions

PEFT 0.19.1
Transformers 5.14.0
Pytorch 2.11.0+cu128
Datasets 5.0.0
Tokenizers 0.22.2