greenw0lf's picture
update model card README.md
1b7d49d
|
raw
history blame
2.57 kB
metadata
license: apache-2.0
tags:
  - generated_from_trainer
datasets:
  - common_voice_8_0
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xls-r-1b-frisian-cv-8-10m
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_8_0
          type: common_voice_8_0
          config: fy-NL
          split: validation
          args: fy-NL
        metrics:
          - name: Wer
            type: wer
            value: 0.8409155834880732

wav2vec2-large-xls-r-1b-frisian-cv-8-10m

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on the common_voice_8_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 1.2060
  • Wer: 0.8409

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: 7e-05
  • train_batch_size: 16
  • eval_batch_size: 8
  • seed: 42
  • optimizer: Adam with betas=(0.9,0.98) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • num_epochs: 90
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
13.1755 6.25 50 4.7246 0.9927
8.0106 12.5 100 3.8216 0.9996
3.4536 18.75 150 3.0254 1.0
3.1828 25.0 200 2.9839 1.0
3.1087 31.25 250 2.9887 1.0
3.0176 37.5 300 2.8903 1.0
2.912 43.75 350 2.6903 1.0
2.7648 50.0 400 2.1968 1.0016
2.1665 56.25 450 1.6039 0.9838
1.8149 62.5 500 1.3367 0.9484
1.6385 68.75 550 1.2353 0.9340
1.314 75.0 600 1.2081 0.8834
1.0963 81.25 650 1.2016 0.8416
1.2322 87.5 700 1.2060 0.8409

Framework versions

  • Transformers 4.28.1
  • Pytorch 2.0.0+cu117
  • Datasets 2.11.0
  • Tokenizers 0.13.3