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Dahn/
wav2vec2-large-xls-r-300m-turkish-colab

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

automatic-speech-recognition

generated_from_trainer

common_voice

apache-2.0

endpoints_compatible

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wav2vec2-large-xls-r-300m-turkish-colab

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

Loss: 0.3965
Wer: 0.3807

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
3.974	3.67	400	0.7102	0.7318
0.4216	7.34	800	0.4273	0.4941
0.1891	11.01	1200	0.4548	0.4864
0.1267	14.68	1600	0.4208	0.4082
0.0958	18.35	2000	0.4236	0.4033
0.0799	22.02	2400	0.4052	0.3829
0.0624	25.69	2800	0.4088	0.3875
0.0491	29.36	3200	0.3965	0.3807

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.18.3
Tokenizers 0.10.3

Dahn/wav2vec2-large-xls-r-300m-turkish-colab

wav2vec2-large-xls-r-300m-turkish-colab

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Dahn/
wav2vec2-large-xls-r-300m-turkish-colab