bart-base-summarization-medical-51 – AI Model by zbigi | AlphaNeural AI

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zbigi/
bart-base-summarization-medical-51

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facebook/bart-base

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bart-base-summarization-medical-51

This model is a fine-tuned version of facebook/bart-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 2.1339
Rouge1: 0.4189
Rouge2: 0.2237
Rougel: 0.356
Rougelsum: 0.3558
Gen Len: 18.191

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: 3e-05
train_batch_size: 4
eval_batch_size: 1
seed: 51
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 6
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
2.7175	1.0	1250	2.2013	0.4107	0.219	0.35	0.3496	17.772
2.5872	2.0	2500	2.1674	0.4158	0.2228	0.3536	0.3531	18.005
2.5979	3.0	3750	2.1502	0.415	0.2215	0.351	0.3509	18.111
2.5579	4.0	5000	2.1428	0.4178	0.226	0.3548	0.3549	18.143
2.5332	5.0	6250	2.1350	0.4172	0.2243	0.3546	0.3542	18.149
2.5331	6.0	7500	2.1339	0.4189	0.2237	0.356	0.3558	18.191

Framework versions

PEFT 0.12.0
Transformers 4.42.4
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1