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finetune – AI Model by binhduong2310 | AlphaNeural AI
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binhduong2310
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finetune
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transformers
pytorch
tensorboard
bart
text2text-generation
generated_from_trainer
mit
endpoints_compatible
us
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finetune
This model is a fine-tuned version of
hoabinh/finetune
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 0.7561
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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
total_train_batch_size: 16
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 500
num_epochs: 1
Training results
Training Loss
Epoch
Step
Validation Loss
0.3381
0.29
200
0.7756
0.4382
0.59
400
0.8077
0.3142
0.88
600
0.7561
Framework versions
Transformers 4.23.1
Pytorch 1.12.1+cu113
Datasets 2.6.1
Tokenizers 0.13.1