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mt5-small-finetuned-amazon-en-es
EhtashamNQ/mt5-small-finetuned-amazon-en-es
mt5-small-finetuned-amazon-en-es is a machine learning model from EhtashamNQ. 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.
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
- Nov 10, 2022
- Updated
- Nov 11, 2022
- SHA
- 0b4e9e91
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information Keras had access to. You should
probably proofread and complete it, then remove this comment. -->
EhtashamNQ/mt5-small-finetuned-amazon-en-es
This model is a fine-tuned version of google/mt5-small on an unknown dataset. It achieves the following results on the evaluation set:
- Train Loss: 2.5396
- Validation Loss: 2.8061
- Epoch: 5
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:
- optimizer: {'name': 'AdamWeightDecay', 'learning_rate': {'class_name': 'PolynomialDecay', 'config': {'initial_learning_rate': 5.6e-05, 'decay_steps': 5208, 'end_learning_rate': 0.0, 'power': 1.0, 'cycle': False, 'name': None}}, 'decay': 0.0, 'beta_1': 0.9, 'beta_2': 0.999, 'epsilon': 1e-08, 'amsgrad': False, 'weight_decay_rate': 0.01}
- training_precision: mixed_float16
Training results
| Train Loss | Validation Loss | Epoch |
|---|---|---|
| 20.5300 | 7.1775 | 0 |
| 5.5220 | 3.7545 | 1 |
| 3.4137 | 3.5929 | 2 |
| 2.9827 | 3.0892 | 3 |
| 2.7228 | 2.8718 | 4 |
| 2.5396 | 2.8061 | 5 |
Framework versions
- Transformers 4.24.0
- TensorFlow 2.9.2
- Datasets 2.6.1
- Tokenizers 0.13.2
- Library
- transformers
- Type
- mt5
- License
- apache-2.0
- Created
- Nov 10, 2022
- Updated
- Nov 11, 2022