wav2vec2-1b-E50_freq_pause – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-1b-E50_freq_pause

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-E50_freq_pause

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: 0.8597
Cer: 24.3832

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
15.9037	0.2580	200	5.1166	92.5458
11.4762	0.5160	400	11.0693	93.5092
5.6392	0.7741	600	4.8196	92.3990
4.5741	1.0321	800	4.5280	92.4988
4.5003	1.2901	1000	4.4228	91.0421
4.4138	1.5481	1200	4.3815	91.8233
4.3121	1.8062	1400	4.2013	81.1560
4.2003	2.0642	1600	4.5168	89.6617
4.0984	2.3222	1800	4.3367	87.5059
4.0011	2.5802	2000	4.0720	77.6668
3.8311	2.8383	2200	4.1406	80.9269
3.425	3.0963	2400	3.0046	62.9347
2.1444	3.3543	2600	1.8194	41.1948
1.4272	3.6123	2800	1.4620	36.2371
1.1442	3.8703	3000	1.1785	30.7272
0.9262	4.1284	3200	1.1745	32.0841
0.7623	4.3864	3400	0.9678	27.3026
0.7033	4.6444	3600	0.9814	27.2968
0.6478	4.9024	3800	0.8597	24.3832

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1