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wav2vec2-large-xls-r-300m-wolof-test-coloab

Automatic Speech Recognition

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wav2vec2-large-xls-r-300m-wolof-test-coloab

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.3573
Wer: 0.3532

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
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
3.6106	14.29	400	0.4260	0.4630
0.215	28.57	800	0.3573	0.3532

Framework versions

Transformers 4.27.0
Pytorch 1.10.0+cu113
Datasets 1.18.3
Tokenizers 0.13.2

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Safetensors

Model size

315M params

Tensor type

F32

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Automatic Speech Recognition

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Evaluation results

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