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kgBolt/
story_summarizer-finetuned

Name: story_summarizer-finetuned
Availability: InStock

generated_from_trainer

mit

endpoints_compatible

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story_summarizer-finetuned

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

Loss: 2.9028
Rouge1: 30.4344
Rouge2: 6.2601
Rougel: 18.9971
Rougelsum: 26.4496
Gen Len: 95.0942

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Rouge1	Rouge2	Rougel	Rougelsum	Gen Len
No log	1.0	150	2.8526	29.1919	5.8045	18.2639	25.4635	102.0117
No log	2.0	300	2.8654	30.0355	6.0614	18.7598	26.1234	96.4292
No log	3.0	450	2.9028	30.4344	6.2601	18.9971	26.4496	95.0942

Framework versions

Transformers 4.27.4
Pytorch 2.0.0+cu118
Datasets 2.11.0
Tokenizers 0.13.2

kgBolt/story_summarizer-finetuned

story_summarizer-finetuned

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

kgBolt/
story_summarizer-finetuned