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pinot/
wav2vec2-large-xls-r-300m-ja-colab

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

automatic-speech-recognition

generated_from_trainer

common_voice_10_0

apache-2.0

endpoints_compatible

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wav2vec2-large-xls-r-300m-ja-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: 1.1407
Wer: 0.2456

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 16
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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	1.0	637	5.3238	0.9663
No log	2.0	1274	4.1785	0.7662
No log	3.0	1911	2.3701	0.4983
No log	4.0	2548	1.8443	0.4090
6.5781	5.0	3185	1.4892	0.3363
6.5781	6.0	3822	1.3229	0.2995
6.5781	7.0	4459	1.2418	0.2814
6.5781	8.0	5096	1.1928	0.2647
1.0184	9.0	5733	1.1584	0.2520
1.0184	10.0	6370	1.1407	0.2456

Framework versions

Transformers 4.21.2
Pytorch 1.10.0+cu113
Datasets 2.4.0
Tokenizers 0.12.1

pinot/wav2vec2-large-xls-r-300m-ja-colab

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

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

pinot/
wav2vec2-large-xls-r-300m-ja-colab