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DunnBC22/
distilbert-base-multilingual-cased-language_detection

Name: distilbert-base-multilingual-cased-language_detection
Availability: InStock

generated_from_trainer

apache-2.0

autotrain_compatible

endpoints_compatible

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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: 0.0595
Accuracy: 0.9971
F1
- Weighted: 0.9971
- Micro: 0.9971
- Macro: 0.9977
Recall
- Weighted: 0.9971
- Micro: 0.9971
- Macro: 0.9974
Precision
- Weighted: 0.9971
- Micro: 0.9971
- Macro: 0.9981

Model description

This is a classification model of 16 different languages.

For more information on how it was created, check out the following link: https://github.com/DunnBC22/NLP_Projects/blob/main/Language%20Detection/Language%20Detection-%2010k%20Samples/language_detection-10k.ipynb

Intended uses & limitations

This model is intended to demonstrate my ability to solve a complex problem using technology.

Training and evaluation data

Dataset Source: https://www.kaggle.com/datasets/basilb2s/language-detection

Input Word Length:

Input Word Length By Class:

Length of Input Text (in Words) By Class

Class Distribution:

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: 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	Accuracy	Weighted F1	Micro F1	Macro F1	Weighted Recall	Micro Recall	Macro Recall	Weighted Precision	Micro Precision	Macro Precision
1.0783	1.0	128	0.1544	0.9823	0.9819	0.9823	0.9806	0.9823	0.9823	0.9798	0.9847	0.9823	0.9852
0.1189	2.0	256	0.0595	0.9971	0.9971	0.9971	0.9977	0.9971	0.9971	0.9974	0.9971	0.9971	0.9981
0.0651	3.0	384	0.0473	0.9971	0.9971	0.9971	0.9977	0.9971	0.9971	0.9974	0.9971	0.9971	0.9981

Framework versions

Transformers 4.26.1
Pytorch 1.12.1
Datasets 2.9.0
Tokenizers 0.12.1

License Notice

This model is a fine-tuned derivative of a pretrained model. Users must comply with the original model license.

Dataset Notice

This model was fine-tuned on third-party datasets which may have separate licenses or usage restrictions.

DunnBC22/distilbert-base-multilingual-cased-language_detection