wav2vec-xlsr-ft-cy-verbatim – AI Model by techiaith | AlphaNeural AI

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techiaith/
wav2vec-xlsr-ft-cy-verbatim

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automatic-speech-recognition

techiaith/banc-trawsgrifiadau-bangor

generated_from_trainer

banc-trawsgrifiadau-bangor

endpoints_compatible

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wav2vec2-xlsr-ft-cy-verbatim

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

Loss: 0.4357
Wer: 0.3262

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: 5.0
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
No log	0.21	100	3.4135	1.0
No log	0.41	200	2.9521	1.0
No log	0.62	300	2.3339	0.9365
No log	0.83	400	1.2433	0.8259
3.1912	1.03	500	0.8614	0.6385
3.1912	1.24	600	0.7557	0.5612
3.1912	1.44	700	0.6781	0.5195
3.1912	1.65	800	0.6363	0.4879
3.1912	1.86	900	0.5959	0.4559
0.8237	2.06	1000	0.5430	0.4260
0.8237	2.27	1100	0.5293	0.4098
0.8237	2.48	1200	0.5141	0.4056
0.8237	2.68	1300	0.4879	0.3947
0.8237	2.89	1400	0.4697	0.3788
0.5625	3.1	1500	0.4748	0.3780
0.5625	3.3	1600	0.4836	0.3684
0.5625	3.51	1700	0.4796	0.3625
0.5625	3.72	1800	0.4582	0.3515
0.5625	3.92	1900	0.4395	0.3437
0.4267	4.13	2000	0.4410	0.3420
0.4267	4.33	2100	0.4467	0.3382
0.4267	4.54	2200	0.4398	0.3329
0.4267	4.75	2300	0.4383	0.3287
0.4267	4.95	2400	0.4358	0.3264

Framework versions

Transformers 4.28.1
Pytorch 2.0.0+cu117
Datasets 2.11.0
Tokenizers 0.13.3