wav2vec2-base-cynthia-tedlium-2500-v2 – AI Model by huyue012 | AlphaNeural AI

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huyue012/
wav2vec2-base-cynthia-tedlium-2500-v2

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wav2vec2-base-cynthia-tedlium-2500-v2

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the None dataset. It achieves the following results on the evaluation set:

Loss: 0.6425
Wer: 0.2033

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: 16
eval_batch_size: 8
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 32
optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
lr_scheduler_type: linear
lr_scheduler_warmup_steps: 1000
num_epochs: 50
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.1196	6.58	500	0.6498	0.2103
0.1176	13.16	1000	0.6490	0.2169
0.1227	19.73	1500	0.6241	0.2127
0.1078	26.31	2000	0.6359	0.2118
0.0956	32.89	2500	0.6330	0.2073
0.1008	39.47	3000	0.6816	0.2036
0.09	46.05	3500	0.6425	0.2033

Framework versions

Transformers 4.11.3
Pytorch 1.10.0+cu113
Datasets 1.13.3
Tokenizers 0.10.3