README.md

metadata

license: apache-2.0
tags:
  - generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
    results:
      - task:
          type: automatic-speech-recognition
          name: Automatic Speech Recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: id
          split: test
          args: id
        metrics:
          - type: wer
            value: 0.9777378318584071
            name: Wer

wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11

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

• Loss: 1.3207
• Wer: 0.9777

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: 0.001
• train_batch_size: 16
• eval_batch_size: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• num_epochs: 5
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	464	2.8781	1.0
3.005	2.0	928	2.5395	1.0
2.7477	3.0	1392	1.6528	0.9993
1.9398	4.0	1856	1.3991	0.9854
1.4528	5.0	2320	1.3207	0.9777

Framework versions

• Transformers 4.39.3
• Pytorch 2.2.2+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2