metadata

license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: XLS-R-demo-google-colab-Ezra_William_Prod_3
    results:
      - task:
          name: Automatic Speech Recognition
          type: automatic-speech-recognition
        dataset:
          name: common_voice_13_0
          type: common_voice_13_0
          config: id
          split: validation
          args: id
        metrics:
          - name: Wer
            type: wer
            value: 0.697900059217419

XLS-R-demo-google-colab-Ezra_William_Prod_3

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: 0.7896
Wer: 0.6979

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: 0.0001
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: 12
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.4479	1.0	121	2.9741	1.0
2.9543	2.0	242	2.9297	1.0
2.9306	3.0	363	2.9112	1.0
2.9216	4.0	484	2.9071	1.0
2.8968	5.0	605	2.8713	1.0
2.8822	6.0	726	2.8446	1.0
2.8421	7.0	847	2.5157	1.0
2.5763	8.0	968	1.5780	0.9964
1.9449	9.0	1089	0.9864	0.8132
1.0398	10.0	1210	0.8565	0.7348
0.9162	11.0	1331	0.7941	0.7043
0.8909	12.0	1452	0.7896	0.6979

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1