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metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: w2v-bert-cv-grain-lg_both
    results: []

w2v-bert-cv-grain-lg_both

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

  • Loss: 16.2243
  • Wer: 1.0
  • Cer: 1.0

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: 8
  • eval_batch_size: 4
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • num_epochs: 100
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer Cer
0.4609 1.0 5406 0.1400 0.1423 0.0296
0.2829 2.0 10812 0.1133 0.0968 0.0213
0.2369 3.0 16218 0.1033 0.0883 0.0193
0.2106 4.0 21624 0.0848 0.0681 0.0162
0.197 5.0 27030 0.0871 0.0681 0.0159
0.2459 6.0 32436 0.1335 0.1022 0.0203
0.3563 7.0 37842 0.1809 0.1254 0.0267
0.6033 8.0 43248 0.5575 0.7032 0.1768
4.656 9.0 48654 16.9063 0.9980 0.9837
10.5595 10.0 54060 12.4706 1.0 1.0
17.1148 11.0 59466 16.2280 1.0 1.0
17.4223 12.0 64872 16.2273 1.0 1.0
17.4172 13.0 70278 16.2222 1.0 1.0
17.4159 14.0 75684 16.2243 1.0 1.0

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.1.0+cu118
  • Datasets 3.1.0
  • Tokenizers 0.20.1