wav2vec2-E30_freq – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-E30_freq

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-300m

endpoints_compatible

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wav2vec2-E30_freq

This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on an unknown dataset. It achieves the following results on the evaluation set:

Loss: 1.1100
Cer: 25.3231

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: 8
eval_batch_size: 8
seed: 42
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 50
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Cer
36.3999	0.1289	200	5.2146	100.0
4.9737	0.2579	400	4.6959	100.0
4.8	0.3868	600	4.6382	100.0
4.7654	0.5158	800	4.6577	100.0
4.7312	0.6447	1000	4.6288	100.0
4.6911	0.7737	1200	4.5862	100.0
4.6383	0.9026	1400	4.4792	98.2672
4.5195	1.0316	1600	4.2400	97.1511
3.9204	1.1605	1800	3.1009	56.4850
2.9139	1.2895	2000	2.5245	45.1539
2.5171	1.4184	2200	2.2244	43.6090
2.2497	1.5474	2400	1.9096	36.6306
2.0305	1.6763	2600	1.7620	34.7568
1.8039	1.8053	2800	1.6661	34.1988
1.7213	1.9342	3000	1.5361	32.5012
1.6193	2.0632	3200	1.4061	30.2690
1.4749	2.1921	3400	1.3094	29.5054
1.3899	2.3211	3600	1.2938	28.8299
1.3117	2.4500	3800	1.2227	27.3672
1.3021	2.5790	4000	1.1946	26.9854
1.2421	2.7079	4200	1.1484	26.1337
1.1926	2.8369	4400	1.1358	25.9575
1.1854	2.9658	4600	1.1100	25.3231

Framework versions

Transformers 4.44.2
Pytorch 2.4.1+cu121
Datasets 3.0.1
Tokenizers 0.19.1