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

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Gummybear05/
wav2vec2-1b-Yfreq_pause_speed

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-Yfreq_pause_speed

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: 1.1898
Cer: 31.1501

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
10.7019	0.2580	200	5.2871	100.0
2.9862	0.5160	400	2.5816	61.0021
1.4741	0.7741	600	2.3005	54.0120
1.1621	1.0321	800	1.7372	43.0569
0.9078	1.2901	1000	1.5138	38.3459
0.8152	1.5481	1200	1.5787	43.2566
0.7734	1.8062	1400	1.5237	40.7307
0.639	2.0642	1600	1.5034	37.8759
0.5611	2.3222	1800	1.4911	38.7277
0.5272	2.5802	2000	1.3679	37.0418
0.4739	2.8383	2200	1.5056	41.7469
0.4307	3.0963	2400	1.2907	34.7568
0.3732	3.3543	2600	1.4109	36.4250
0.3388	3.6123	2800	1.3857	37.1299
0.3089	3.8703	3000	1.2816	33.6760
0.2648	4.1284	3200	1.2267	32.7596
0.2299	4.3864	3400	1.2182	32.3896
0.2108	4.6444	3600	1.1818	31.1090
0.2055	4.9024	3800	1.1898	31.1501

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1