wav2vec2-1b-E50_speed – AI Model by Gummybear05 | AlphaNeural AI

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Gummybear05/
wav2vec2-1b-E50_speed

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automatic-speech-recognition

generated_from_trainer

facebook/wav2vec2-xls-r-1b

endpoints_compatible

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wav2vec2-1b-E50_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: 0.5794
Cer: 21.1466

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
22.602	0.2580	200	6.2336	100.0
4.8547	0.5160	400	4.5853	98.3318
4.6154	0.7741	600	4.6172	93.2331
4.4727	1.0321	800	4.3835	80.8506
4.2854	1.2901	1000	4.2819	77.9194
3.947	1.5481	1200	3.1503	61.7070
2.091	1.8062	1400	1.7032	40.4547
1.223	2.0642	1600	1.4472	39.8320
0.8867	2.3222	1800	1.2054	30.8506
0.7444	2.5802	2000	1.0326	31.4732
0.6529	2.8383	2200	0.8416	27.4671
0.5313	3.0963	2400	0.8239	25.0176
0.4148	3.3543	2600	0.7047	24.6417
0.3665	3.6123	2800	0.6761	22.5681
0.3435	3.8703	3000	0.6632	22.3567
0.2865	4.1284	3200	0.5879	21.1936
0.2307	4.3864	3400	0.6009	21.3875
0.2198	4.6444	3600	0.5810	21.2700
0.195	4.9024	3800	0.5794	21.1466

Framework versions

Transformers 4.45.2
Pytorch 2.3.1.post100
Datasets 2.19.1
Tokenizers 0.20.1