wav2vec2-base_toy_train_data_random_high_pass – AI Model by scasutt | AlphaNeural AI

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wav2vec2-base_toy_train_data_random_high_pass

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wav2vec2-base_toy_train_data_random_high_pass

This model is a fine-tuned version of facebook/wav2vec2-base on the None dataset. It achieves the following results on the evaluation set:

Loss: 1.2841
Wer: 0.7222

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
gradient_accumulation_steps: 2
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: 1000
num_epochs: 20

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.061	2.1	500	3.0551	1.0
1.1294	4.2	1000	1.3102	0.8777
0.7051	6.3	1500	1.2081	0.8092
0.5421	8.4	2000	1.2280	0.7684
0.448	10.5	2500	1.2459	0.7506
0.3777	12.6	3000	1.3533	0.7631
0.3611	14.7	3500	1.2058	0.7291
0.3177	16.81	4000	1.3168	0.7185
0.279	18.91	4500	1.2841	0.7222

Framework versions

Transformers 4.17.0
Pytorch 1.11.0+cu102
Datasets 2.0.0
Tokenizers 0.11.6