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ft-facebook-bart-large-xsum-on-samsum – AI Model by mrami010 | AlphaNeural AI
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ft-facebook-bart-large-xsum-on-samsum
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-large-xsum
finetune
mit
endpoints_compatible
us
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ft-facebook-bart-large-xsum-on-samsum
This model is a fine-tuned version of
facebook/bart-large-xsum
on the None dataset. It achieves the following results on the evaluation set:
Loss: 1.5249
Rouge1: 50.3616
Rouge2: 25.1246
Rougel: 41.214
Rougelsum: 46.1946
Gen Len: 26.423
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
gradient_accumulation_steps: 4
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
training_steps: 100
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
Rouge1
Rouge2
Rougel
Rougelsum
Gen Len
No log
0.11
100
1.5514
49.1738
23.682
40.0793
44.8382
26.0818
Framework versions
Transformers 4.37.2
Pytorch 2.2.1+cu121
Datasets 2.17.0
Tokenizers 0.15.2
