wav2vec2-base-timit-finetune-3 – AI Model by rohitp1 | AlphaNeural AI

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rohitp1/
wav2vec2-base-timit-finetune-3

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wav2vec2-base-timit-finetune-3

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: 0.4387
Wer: 0.2750

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: 32
eval_batch_size: 32
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 64
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 60
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4692	6.94	500	0.9978	0.7091
0.3946	13.88	1000	0.3674	0.3253
0.1291	20.83	1500	0.3987	0.3042
0.074	27.77	2000	0.4292	0.2916
0.0487	34.72	2500	0.4302	0.2853
0.0368	41.66	3000	0.4222	0.2789
0.0281	48.61	3500	0.4481	0.2783
0.0237	55.55	4000	0.4387	0.2750

Framework versions

Transformers 4.24.0
Pytorch 1.12.1
Datasets 2.7.0
Tokenizers 0.11.0