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pinot/
wav2vec2-large-xls-r-300m-j-phoneme-colab

Name: wav2vec2-large-xls-r-300m-j-phoneme-colab
Availability: InStock

transformers

pytorch

wav2vec2

automatic-speech-recognition

generated_from_trainer

common_voice_10_0

apache-2.0

endpoints_compatible

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wav2vec2-large-xls-r-300m-j-phoneme-colab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice_10_0 dataset. It achieves the following results on the evaluation set:

Loss: 0.5212
Wer: 0.2998

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: 4
eval_batch_size: 4
seed: 42
gradient_accumulation_steps: 4
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
0.7364	3.0	2000	0.4703	0.4503
0.5673	6.01	4000	0.4585	0.3855
0.5048	9.01	6000	0.4567	0.3543
0.4567	12.01	8000	0.4433	0.3473
0.4194	15.02	10000	0.4491	0.3386
0.3905	18.02	12000	0.4829	0.3360
0.3644	21.02	14000	0.5032	0.3306
0.3441	24.02	16000	0.5242	0.3389
0.2589	27.03	18000	0.5212	0.2998

Framework versions

Transformers 4.22.2
Pytorch 1.10.0+cu113
Datasets 2.5.1
Tokenizers 0.12.1

pinot/wav2vec2-large-xls-r-300m-j-phoneme-colab

wav2vec2-large-xls-r-300m-j-phoneme-colab

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

pinot/
wav2vec2-large-xls-r-300m-j-phoneme-colab