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masapasa/
xls-r-300m-it-cv8-ds13

Name: xls-r-300m-it-cv8-ds13
Availability: InStock

transformers

pytorch

wav2vec2

automatic-speech-recognition

generated_from_trainer

hf-asr-leaderboard

mozilla-foundation/common_voice_8_0

robust-speech-event

mozilla-foundation/common_voice_8_0

apache-2.0

endpoints_compatible

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This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - SV-SE dataset. It achieves the following results on the evaluation set:

Loss: 0.3549
Wer: 0.3827

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: 7.5e-05
train_batch_size: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 128
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 2000
num_epochs: 50.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4129	5.49	500	3.3224	1.0
2.9323	10.98	1000	2.9128	1.0000
1.6839	16.48	1500	0.7740	0.6854
1.485	21.97	2000	0.5830	0.5976
1.362	27.47	2500	0.4866	0.4905
1.2752	32.96	3000	0.4240	0.4967
1.1957	38.46	3500	0.3899	0.4258
1.1646	43.95	4000	0.3597	0.4014
1.1265	49.45	4500	0.3559	0.3829

Framework versions

Transformers 4.17.0.dev0
Pytorch 1.10.2+cu102
Datasets 1.18.3
Tokenizers 0.11.0

masapasa/xls-r-300m-it-cv8-ds13

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

masapasa/
xls-r-300m-it-cv8-ds13