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E2G-Web
jquigl/E2G-Web
E2G-Web is a machine learning model from jquigl. 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 mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- transformers
- License
- mit
- Model type
- m2m_100
- Access
- Public
- Created
- Feb 15, 2025
- Updated
- Feb 15, 2025
- SHA
- 6c531e16
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. -->
M2M_Web_en-ga_fixed
This model is a fine-tuned version of facebook/m2m100_418M on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1600
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 7182
- optimizer: Use adafactor and the args are: No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.1918 | 1.0 | 150030 | 0.1850 |
| 0.1725 | 2.0 | 300060 | 0.1667 |
| 0.1605 | 3.0 | 450090 | 0.1600 |
Framework versions
- Transformers 4.48.1
- Pytorch 2.4.0
- Datasets 2.19.1
- Tokenizers 0.21.0
- Library
- transformers
- Type
- m2m_100
- License
- mit
- Created
- Feb 15, 2025
- Updated
- Feb 15, 2025