metadata

license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
  - generated_from_trainer
datasets:
  - common_voice_13_0
metrics:
  - wer
model-index:
  - name: XLS-R-demo-google-colab-Ezra_William_Prod_2
    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: 0.7214503712476654

XLS-R-demo-google-colab-Ezra_William_Prod_2

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_13_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.8224
Wer: 0.7215

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
5.1374	1.0	121	2.9882	1.0
2.9639	2.0	242	2.9334	1.0
2.9322	3.0	363	2.9144	1.0
2.9198	4.0	484	2.9017	1.0
2.8947	5.0	605	2.8740	1.0
2.8716	6.0	726	2.8349	0.9999
2.8277	7.0	847	2.5051	1.0
2.5331	8.0	968	1.4294	0.9178
1.6883	9.0	1089	0.9830	0.7981
0.9526	10.0	1210	0.8735	0.7564
0.8469	11.0	1331	0.8294	0.7308
0.83	12.0	1452	0.8224	0.7215

Framework versions

Transformers 4.42.3
Pytorch 2.3.1+cu121
Datasets 2.20.0
Tokenizers 0.19.1