fine_tuned_bert / README.md
morten-j's picture
morten-j/fine_tuned_mBERT
efbff09 verified
metadata
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
  - generated_from_trainer
metrics:
  - f1
  - precision
  - recall
model-index:
  - name: fine_tuned_bert
    results: []

fine_tuned_bert

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

  • Loss: 0.1299
  • F1: 0.8444
  • F5: 0.8373
  • Precision: 0.8636
  • Recall: 0.8261

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: 64
  • eval_batch_size: 64
  • seed: 42
  • distributed_type: multi-GPU
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • num_epochs: 10
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss F1 F5 Precision Recall
No log 1.0 33 0.3776 0.0 0.0 0.0 0.0
No log 2.0 66 0.2996 0.4 0.3359 0.8 0.2667
No log 3.0 99 0.2137 0.7273 0.7534 0.6667 0.8
No log 4.0 132 0.2161 0.6429 0.6258 0.6923 0.6
No log 5.0 165 0.2367 0.6154 0.5812 0.7273 0.5333
No log 6.0 198 0.1997 0.7451 0.6980 0.9048 0.6333
No log 7.0 231 0.2023 0.8000 0.8 0.8 0.8
No log 8.0 264 0.2011 0.8070 0.7911 0.8519 0.7667
No log 9.0 297 0.2196 0.7857 0.7648 0.8462 0.7333
No log 10.0 330 0.2509 0.7667 0.7667 0.7667 0.7667

Framework versions

  • Transformers 4.38.2
  • Pytorch 2.3.0a0+ebedce2
  • Datasets 2.17.1
  • Tokenizers 0.15.2