bart-samsum – AI Model by ThanhDVi | AlphaNeural AI

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ThanhDVi/
bart-samsum

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text2text-generation

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bart-samsum

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

Loss: 1.5071
Rouge1: 0.4835
Rouge2: 0.2546
Rougel: 0.4128
Rougelsum: 0.4131
Gen Len: 17.9817

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: 4
eval_batch_size: 4
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 4
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
1.8082	1.0	2947	1.5613	0.4763	0.2412	0.4043	0.4041	17.9332
1.5609	2.0	5894	1.5206	0.4827	0.2485	0.4082	0.4085	18.3169
1.4228	3.0	8841	1.5008	0.4851	0.2557	0.4138	0.4137	17.9851
1.3131	4.0	11788	1.5071	0.4835	0.2546	0.4128	0.4131	17.9817

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu118
Datasets 2.12.0
Tokenizers 0.13.3