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metadata
base_model: ylacombe/w2v-bert-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: w2v-bert-2.0-dutch-colab-CV16.0
    results: []

w2v-bert-2.0-dutch-colab-CV16.0

This model is a fine-tuned version of ylacombe/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:

  • Loss: 0.0920
  • Wer: 0.0573

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: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 128
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 5
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
1.3106 1.0 358 0.1833 0.1350
0.0924 2.0 716 0.1365 0.0932
0.0521 3.0 1074 0.1121 0.0732
0.033 3.99 1432 0.0957 0.0619
0.0221 4.99 1790 0.0920 0.0573

Framework versions

  • Transformers 4.37.0.dev0
  • Pytorch 1.12.1+cu116
  • Datasets 2.4.0
  • Tokenizers 0.15.2