BART_1st_STAGE_SUMMARIZER – AI Model by jgibb | AlphaNeural AI

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jgibb/
BART_1st_STAGE_SUMMARIZER

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text2text-generation

generated_from_trainer

facebook/bart-large

endpoints_compatible

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BART_1st_STAGE_SUMMARIZER

This model is a fine-tuned version of facebook/bart-large on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1826
Rouge1: 0.7384
Rouge2: 0.5134
Rougel: 0.6809
Rougelsum: 0.6852
Wer: 0.3923

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: 6
eval_batch_size: 6
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	Wer
No log	0.21	250	1.3973	0.7211	0.486	0.6611	0.6661	0.417
1.969	0.42	500	1.2499	0.7303	0.4988	0.67	0.6745	0.4056
1.969	0.63	750	1.2039	0.734	0.5068	0.6761	0.6798	0.3977
1.3659	0.84	1000	1.1826	0.7384	0.5134	0.6809	0.6852	0.3923

Framework versions

Transformers 4.38.2
Pytorch 2.2.1+cu121
Datasets 2.18.0
Tokenizers 0.15.2