bart-pt-asqa-cb – AI Model by din0s | AlphaNeural AI

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bart-pt-asqa-cb

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bart-pt-asqa-cb

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

Loss: 2.5362
Rougelsum: 38.9467

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: 5e-06
train_batch_size: 16
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 20
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rougelsum
No log	1.0	273	2.5653	37.6939
2.6009	2.0	546	2.5295	38.2398
2.6009	3.0	819	2.5315	38.5946
2.3852	4.0	1092	2.5146	38.4771
2.3852	5.0	1365	2.5240	38.5706
2.2644	6.0	1638	2.5253	38.7506
2.2644	7.0	1911	2.5355	38.9004
2.1703	8.0	2184	2.5309	38.9528
2.1703	9.0	2457	2.5362	38.9467

Framework versions

Transformers 4.23.0.dev0
Pytorch 1.12.1+cu102
Datasets 2.4.0
Tokenizers 0.12.1