wav2vec2-base-self-331-colab

This model is a fine-tuned version of facebook/wav2vec2-base-960h on the audiofolder dataset. It achieves the following results on the evaluation set:

• Loss: 0.3282
• Wer: 0.1501

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: 1e-05
• 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: 500
• num_epochs: 300
• mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
2.3444	30.77	200	2.1940	0.9841
1.972	61.54	400	1.4582	0.8167
1.3875	92.31	600	0.8476	0.5902
0.9092	123.08	800	0.5445	0.3636
0.6382	153.85	1000	0.4129	0.2641
0.5789	184.62	1200	0.3497	0.1876
0.4632	215.38	1400	0.3478	0.1616
0.4474	246.15	1600	0.3394	0.1486
0.429	276.92	1800	0.3282	0.1501

Framework versions

• Transformers 4.38.2
• Pytorch 2.2.1+cu121
• Datasets 2.18.0
• Tokenizers 0.15.2