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End of training
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metadata
license: apache-2.0
base_model: bert-base-multilingual-uncased
tags:
  - generated_from_trainer
metrics:
  - recall
  - accuracy
model-index:
  - name: multibert_seed34_1611
    results: []

multibert_seed34_1611

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

  • Loss: 0.4810
  • Precisions: 0.8743
  • Recall: 0.8016
  • F-measure: 0.8318
  • Accuracy: 0.9364

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: 7.5e-05
  • train_batch_size: 16
  • eval_batch_size: 16
  • seed: 34
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 14

Training results

Training Loss Epoch Step Validation Loss Precisions Recall F-measure Accuracy
0.4954 1.0 236 0.2579 0.8908 0.7174 0.7485 0.9181
0.2427 2.0 472 0.2589 0.8472 0.7340 0.7497 0.9209
0.1427 3.0 708 0.2844 0.8461 0.7830 0.8096 0.9325
0.0916 4.0 944 0.3453 0.8497 0.7804 0.8122 0.9306
0.0616 5.0 1180 0.3281 0.8500 0.7936 0.8160 0.9303
0.0414 6.0 1416 0.3859 0.8494 0.7930 0.8167 0.9337
0.0272 7.0 1652 0.3863 0.8572 0.7894 0.8167 0.9323
0.0207 8.0 1888 0.3998 0.8525 0.7938 0.8195 0.9337
0.0117 9.0 2124 0.4348 0.8555 0.7983 0.8228 0.9330
0.0089 10.0 2360 0.4858 0.8699 0.7708 0.7996 0.9294
0.0054 11.0 2596 0.4676 0.8559 0.7959 0.8197 0.9344
0.0036 12.0 2832 0.4582 0.8665 0.8038 0.8291 0.9364
0.0025 13.0 3068 0.4810 0.8743 0.8016 0.8318 0.9364
0.0018 14.0 3304 0.4801 0.8685 0.8036 0.8309 0.9366

Framework versions

  • Transformers 4.35.2
  • Pytorch 2.1.0+cu118
  • Datasets 2.15.0
  • Tokenizers 0.15.0