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End of training
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metadata
license: apache-2.0
base_model: distilbert/distilbert-base-multilingual-cased
tags:
  - generated_from_trainer
metrics:
  - accuracy
  - f1
  - precision
  - recall
model-index:
  - name: distilbert-lang-detect
    results: []

distilbert-lang-detect

This model is a fine-tuned version of distilbert/distilbert-base-multilingual-cased on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 0.1215
  • Accuracy: 0.9720
  • F1: 0.9720
  • Precision: 0.9720
  • Recall: 0.9720

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: 5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 42
  • distributed_type: multi-GPU
  • 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 F1 Precision Recall
0.1022 1.0 14547 0.0924 0.9703 0.9703 0.9703 0.9703
0.0783 2.0 29094 0.0924 0.9704 0.9704 0.9705 0.9704
0.0646 3.0 43641 0.1096 0.9724 0.9724 0.9725 0.9724
0.053 4.0 58188 0.1188 0.9722 0.9722 0.9722 0.9722
0.0364 5.0 72735 0.1215 0.9720 0.9720 0.9720 0.9720

Framework versions

  • Transformers 4.39.2
  • Pytorch 2.2.2+cu121
  • Datasets 2.18.0
  • Tokenizers 0.15.0