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mt5-small-denoising – AI Model by Eshan210352R | AlphaNeural AI
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mt5-small-denoising
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transformers
safetensors
mt5
text2text-generation
generated_from_trainer
google/mt5-small
finetune
apache-2.0
endpoints_compatible
us
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mt5-small-denoising
This model is a fine-tuned version of
google/mt5-small
on an unknown dataset. It achieves the following results on the evaluation set:
Loss: 2.9301
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: 2
eval_batch_size: 2
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 8
optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 3
Training results
Training Loss
Epoch
Step
Validation Loss
4.0089
1.0
2500
3.0879
3.7096
2.0
5000
2.9604
3.6368
3.0
7500
2.9301
Framework versions
Transformers 4.56.0
Pytorch 2.8.0+cu126
Datasets 4.0.0
Tokenizers 0.22.0
