wav2vec2-1b-Yspeed – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-1b-Yspeed

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-Yspeed

This model is a fine-tuned version of facebook/wav2vec2-xls-r-1b on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 0.9193
Cer: 22.7561

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: 0.0001
train_batch_size: 2
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 8
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: 50
num_epochs: 5
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
14.1833	0.2580	200	4.5491	97.4389
2.5916	0.5160	400	2.0400	48.7077
1.351	0.7741	600	1.9023	46.5695
1.0665	1.0321	800	1.2533	34.7039
0.8141	1.2901	1000	1.3127	32.2016
0.7672	1.5481	1200	1.3379	33.9814
0.6847	1.8062	1400	1.2278	32.0489
0.5985	2.0642	1600	1.1310	28.4657
0.5208	2.3222	1800	1.2212	29.4995
0.4664	2.5802	2000	1.0708	26.2512
0.4379	2.8383	2200	1.0705	26.3804
0.4332	3.0963	2400	1.0949	27.4260
0.3778	3.3543	2600	0.9809	25.3936
0.3273	3.6123	2800	1.0045	24.5418
0.3117	3.8703	3000	0.9171	23.0146
0.2586	4.1284	3200	0.9051	22.5329
0.2273	4.3864	3400	0.8966	22.3508
0.2169	4.6444	3600	0.9430	23.2202
0.2159	4.9024	3800	0.9193	22.7561

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1