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emre/
wav2vec2-large-xlsr-53-W2V2-TR-MED

Name: wav2vec2-large-xlsr-53-W2V2-TR-MED
Availability: InStock

automatic-speech-recognition

generated_from_trainer

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wav2vec2-large-xlsr-53-W2V2-TR-MED

This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the common_voice dataset. It achieves the following results on the evaluation set:

Loss: 0.4467
Wer: 0.4598

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: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
5.1343	4.21	400	2.3674	1.0372
0.8075	8.42	800	0.4583	0.6308
0.3209	12.63	1200	0.4291	0.5531
0.2273	16.84	1600	0.4348	0.5378
0.1764	21.05	2000	0.4550	0.5326
0.148	25.26	2400	0.4839	0.5319
0.1268	29.47	2800	0.4515	0.5070
0.1113	33.68	3200	0.4590	0.4930
0.1025	37.89	3600	0.4546	0.4888
0.0922	42.11	4000	0.4782	0.4852
0.082	46.32	4400	0.4605	0.4752
0.0751	50.53	4800	0.4358	0.4689
0.0699	54.74	5200	0.4359	0.4629
0.0633	58.95	5600	0.4467	0.4598

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu111
Datasets 1.14.0
Tokenizers 0.10.3

emre/wav2vec2-large-xlsr-53-W2V2-TR-MED

wav2vec2-large-xlsr-53-W2V2-TR-MED

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

emre/
wav2vec2-large-xlsr-53-W2V2-TR-MED