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distilbert-multilingual-uncased-en-de-fr-oct-19
somm/distilbert-multilingual-uncased-en-de-fr-oct-19
distilbert-multilingual-uncased-en-de-fr-oct-19 is a text classification model from somm. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.0273 - F1: 0.9623
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Oct 20, 2022
- Updated
- Nov 7, 2022
- SHA
- e8b7dee9
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Model card
From the Hugging Face model README
distilbert-multilingual-uncased-en-de-fr-oct-19
This model is a fine-tuned version of distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0273
- F1: 0.9623
Model description
This was trained off a cased model, but with .lower() applied to each of the records, if you wish for it to work you must lowercase before inferencing
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: 4e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 0.0573 | 1.0 | 6468 | 0.0364 | 0.9402 |
| 0.0224 | 2.0 | 12936 | 0.0281 | 0.9572 |
| 0.0108 | 3.0 | 19404 | 0.0273 | 0.9623 |
Framework versions
- Transformers 4.23.1
- Pytorch 1.12.1+cu113
- Tokenizers 0.13.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Oct 20, 2022
- Updated
- Nov 7, 2022