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bart-with-asr-noise-sub-0.1 – AI Model by gayanin | AlphaNeural AI
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gayanin
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bart-with-asr-noise-sub-0.1
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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-with-asr-noise-sub-0.1
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: 0.0552
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
Training results
Training Loss
Epoch
Step
Validation Loss
0.1943
0.62
500
0.1056
0.0813
1.24
1000
0.0795
0.0354
1.86
1500
0.0608
0.0169
2.48
2000
0.0552
Framework versions
Transformers 4.37.2
Pytorch 2.1.2+cu121
Datasets 2.17.1
Tokenizers 0.15.2
