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moe-topk-xsum – AI Model by farzanashaju | AlphaNeural AI
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farzanashaju
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moe-topk-xsum
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transformers
safetensors
t5
generated_from_trainer
google-t5/t5-small
finetune
apache-2.0
text-generation-inference
endpoints_compatible
us
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moe-topk
This model is a fine-tuned version of
t5-small
on an unknown dataset.
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: 0.0001
train_batch_size: 2
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
gradient_accumulation_steps: 4
total_train_batch_size: 32
total_eval_batch_size: 32
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
num_epochs: 1
mixed_precision_training: Native AMP
Training results
Framework versions
Transformers 4.50.3
Pytorch 2.3.1+cu118
Datasets 3.6.0
Tokenizers 0.21.4
