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BART_1000samples – AI Model by Imask | AlphaNeural AI

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Imask/
BART_1000samples

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text2text-generation

generated_from_trainer

facebook/bart-large-cnn

endpoints_compatible

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results

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

Loss: 1.7617
Rouge1: 61.3423
Rouge2: 48.0884
Rougel: 49.1785
Rougelsum: 59.1549
Gen Len: 79.92

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-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 300
num_epochs: 2
label_smoothing_factor: 0.1

Training results

Framework versions

Transformers 4.44.2
Pytorch 2.4.0+cu121
Datasets 2.21.0
Tokenizers 0.19.1