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bart-noised-with-all-data – AI Model by gayanin | AlphaNeural AI
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bart-noised-with-all-data
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transformers
safetensors
bart
text2text-generation
generated_from_trainer
facebook/bart-base
finetune
apache-2.0
endpoints_compatible
us
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bart-noised-with-all-data
This model is a fine-tuned version of
facebook/bart-base
on the None dataset. It achieves the following results on the evaluation set:
Loss: 0.3509
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: 16
eval_batch_size: 16
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 10
num_epochs: 3
mixed_precision_training: Native AMP
Training results
Training Loss
Epoch
Step
Validation Loss
0.6261
0.74
500
0.4038
0.3705
1.48
1000
0.3758
0.279
2.22
1500
0.3547
0.2234
2.96
2000
0.3509
Framework versions
Transformers 4.37.2
Pytorch 2.1.2+cu121
Datasets 2.16.1
Tokenizers 0.15.1
