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distilbert-base-multilingual-cased-language_detection
kidusabe/distilbert-base-multilingual-cased-language_detection
distilbert-base-multilingual-cased-language_detection is a text classification model from kidusabe. 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Mar 4, 2025
- Updated
- Mar 5, 2025
- SHA
- 3b06a007
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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. -->
distilbert-base-multilingual-cased-language_detection
This model is a fine-tuned version of distilbert-base-multilingual-cased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.0544
- Accuracy: 0.9912
- Weighted f1: 0.9912
- Micro f1: 0.9912
- Macro f1: 0.9900
- Weighted recall: 0.9912
- Micro recall: 0.9912
- Macro recall: 0.9904
- Weighted precision: 0.9914
- Micro precision: 0.9912
- Macro precision: 0.9899
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Weighted f1 | Micro f1 | Macro f1 | Weighted recall | Micro recall | Macro recall | Weighted precision | Micro precision | Macro precision |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.943 | 1.0 | 128 | 0.1361 | 0.9863 | 0.9863 | 0.9863 | 0.9845 | 0.9863 | 0.9863 | 0.9847 | 0.9868 | 0.9863 | 0.9849 |
| 0.0991 | 2.0 | 256 | 0.0640 | 0.9892 | 0.9893 | 0.9892 | 0.9880 | 0.9892 | 0.9892 | 0.9889 | 0.9896 | 0.9892 | 0.9874 |
| 0.056 | 3.0 | 384 | 0.0544 | 0.9912 | 0.9912 | 0.9912 | 0.9900 | 0.9912 | 0.9912 | 0.9904 | 0.9914 | 0.9912 | 0.9899 |
Framework versions
- Transformers 4.48.3
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 4, 2025
- Updated
- Mar 5, 2025