wav2vec2-base-timit-demo-colab

This model is a fine-tuned version of facebook/wav2vec2-base on the TIMIT dataset. It achieves the following results on the evaluation set:

• Loss: 0.4491
• Wer: 0.3382

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: 8
• seed: 42
• optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
• lr_scheduler_type: linear
• lr_scheduler_warmup_steps: 1000
• num_epochs: 30
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
3.4787	4.0	500	1.4190	0.9939
0.5835	8.0	1000	0.4711	0.4370
0.219	12.0	1500	0.4555	0.3994
0.1251	16.0	2000	0.4515	0.3654
0.0834	20.0	2500	0.4923	0.3564
0.0632	24.0	3000	0.4410	0.3399
0.0491	28.0	3500	0.4491	0.3382

Framework versions

• Transformers 4.11.3
• Pytorch 1.10.0+cu111
• Datasets 1.18.3
• Tokenizers 0.10.3