MBERTbase_REDv2 / README.md
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metadata
library_name: transformers
license: apache-2.0
base_model: google-bert/bert-base-multilingual-cased
tags:
  - generated_from_trainer
metrics:
  - f1
  - accuracy
model-index:
  - name: MBERTbase_REDv2
    results: []

MBERTbase_REDv2

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: 0.3320
  • F1: 0.5326
  • Roc Auc: 0.7058
  • Accuracy: 0.4383

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: 1e-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: 15

Training results

Training Loss Epoch Step Validation Loss F1 Roc Auc Accuracy
No log 1.0 64 0.4206 0.0 0.5 0.0
No log 2.0 128 0.3876 0.0901 0.5328 0.0589
No log 3.0 192 0.3599 0.2983 0.5993 0.2081
No log 4.0 256 0.3434 0.3808 0.6365 0.2965
No log 5.0 320 0.3360 0.4182 0.6474 0.3204
No log 6.0 384 0.3267 0.4638 0.6703 0.3646
No log 7.0 448 0.3259 0.5033 0.6945 0.3959
0.3376 8.0 512 0.3226 0.5140 0.6978 0.4217
0.3376 9.0 576 0.3248 0.5099 0.6959 0.4199
0.3376 10.0 640 0.3252 0.5230 0.6988 0.4162
0.3376 11.0 704 0.3258 0.5211 0.7027 0.4217
0.3376 12.0 768 0.3308 0.5214 0.6998 0.4309
0.3376 13.0 832 0.3304 0.5305 0.7052 0.4383
0.3376 14.0 896 0.3318 0.5297 0.7054 0.4309
0.3376 15.0 960 0.3320 0.5326 0.7058 0.4383

Framework versions

  • Transformers 4.45.1
  • Pytorch 2.4.0
  • Datasets 3.0.1
  • Tokenizers 0.20.0