vishwa27's picture
End of training
597af76
metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53-spanish
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: wav2vec2-large-xls-r-300m-gn
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: gn
          split: test
          args: gn
        metrics:
          - name: Wer
            type: wer
            value: 0.3430613460393091

wav2vec2-large-xls-r-300m-gn

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53-spanish on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

  • Loss: 0.3713
  • Wer: 0.3431

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: 0.0003
  • train_batch_size: 8
  • eval_batch_size: 8
  • seed: 42
  • gradient_accumulation_steps: 2
  • total_train_batch_size: 16
  • optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_steps: 500
  • num_epochs: 30
  • mixed_precision_training: Native AMP

Training results

Training Loss Epoch Step Validation Loss Wer
0.7177 3.62 400 0.3649 0.5816
0.2738 7.24 800 0.4029 0.5024
0.1768 10.86 1200 0.3779 0.4285
0.1128 14.48 1600 0.3929 0.4205
0.0842 18.1 2000 0.3683 0.3916
0.0616 21.72 2400 0.3943 0.3675
0.0461 25.34 2800 0.4127 0.3571
0.0368 28.96 3200 0.3713 0.3431

Framework versions

  • Transformers 4.35.0.dev0
  • Pytorch 2.1.0+cu118
  • Datasets 2.14.6
  • Tokenizers 0.14.1