--- license: apache-2.0 base_model: distilbert-base-multilingual-cased tags: - generated_from_trainer metrics: - accuracy model-index: - name: distilbert-base-multilingual-cased-language-detection-fp16-true results: [] --- # distilbert-base-multilingual-cased-language-detection-fp16-true This model is a fine-tuned version of [distilbert-base-multilingual-cased](https://huggingface.co/distilbert-base-multilingual-cased) on the None dataset. It achieves the following results on the evaluation set: - Loss: 0.0006 - Accuracy: 1.0 - Weighted f1: 1.0 - Micro f1: 1.0 - Macro f1: 1.0 - Weighted recall: 1.0 - Micro recall: 1.0 - Macro recall: 1.0 - Weighted precision: 1.0 - Micro precision: 1.0 - Macro precision: 1.0 ## 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: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### 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 | |:-------------:|:-----:|:----:|:---------------:|:--------:|:-----------:|:--------:|:--------:|:---------------:|:------------:|:------------:|:------------------:|:---------------:|:---------------:| | 0.0814 | 1.0 | 658 | 0.0041 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | 0.9985 | | 0.0063 | 2.0 | 1316 | 0.0011 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | | 0.0008 | 3.0 | 1974 | 0.0006 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | | 0.0001 | 4.0 | 2632 | 0.0013 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | | 0.0001 | 5.0 | 3290 | 0.0013 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9992 | 0.9993 | 0.9992 | 0.9992 | 0.9992 | ### Framework versions - Transformers 4.33.0.dev0 - Pytorch 2.0.1+cu118 - Datasets 2.14.4.dev0 - Tokenizers 0.13.3