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distilled-mt5-base-pseudo-labeling
Lvxue/distilled-mt5-base-pseudo-labeling
distilled-mt5-base-pseudo-labeling is a machine learning model from Lvxue. 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
- mt5
- Access
- Public
- Created
- Aug 24, 2022
- Updated
- Aug 30, 2022
- SHA
- 6d3e9e81
Datasets
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. -->
distilled-mt5-base-pseudo-labeling
This model is a fine-tuned version of google/mt5-small on the Lvxue/wmt16 ro-en dataset. It achieves the following results on the evaluation set:
- Loss: 1.6487
- Bleu: 24.1355
- Gen Len: 44.1211
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: 4
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
Framework versions
- Transformers 4.20.1
- Pytorch 1.12.0+cu102
- Datasets 2.3.2
- Tokenizers 0.12.1
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Languages
- en, ro
- Created
- Aug 24, 2022
- Updated
- Aug 30, 2022