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aakaiser/
bart-cnn-samsum-peft

Name: bart-cnn-samsum-peft
Availability: InStock

peft

tensorboard

safetensors

generated_from_trainer

samsum

aakaiser/bart-cnn-samsum-finetuned

adapter

mit

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bart-cnn-samsum-peft

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

Loss: 0.1361

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: 1e-05
train_batch_size: 8
eval_batch_size: 8
seed: 42
optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 5

Training results

Training Loss	Epoch	Step	Validation Loss
0.0918	1.0	19	0.1363
0.0959	2.0	38	0.1362
0.0916	3.0	57	0.1361
0.0878	4.0	76	0.1361
0.1026	5.0	95	0.1361

Framework versions

PEFT 0.14.0
Transformers 4.50.3
Pytorch 2.6.0+cu124
Datasets 3.5.0
Tokenizers 0.21.1

aakaiser/bart-cnn-samsum-peft

bart-cnn-samsum-peft

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

aakaiser/
bart-cnn-samsum-peft