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moe-hash-xsum
farzanashaju/moe-hash-xsum
moe-hash-xsum is a machine learning model from farzanashaju. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- apache-2.0
- Model type
- t5
- Access
- Public
- Created
- Nov 9, 2025
- Updated
- Nov 9, 2025
- SHA
- c3ba7d76
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
moe-hash
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
- Library
- transformers
- Type
- t5
- License
- apache-2.0
- Created
- Nov 9, 2025
- Updated
- Nov 9, 2025