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

Loss: 3.5903
Accuracy: 0.0612

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: 5e-05
train_batch_size: 36
eval_batch_size: 36
seed: 42
gradient_accumulation_steps: 4
total_train_batch_size: 144
optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
lr_scheduler_type: linear
lr_scheduler_warmup_ratio: 0.1
num_epochs: 3
mixed_precision_training: Native AMP

Training results

Epoch	Step	Validation Loss	Accuracy
1.0	275	3.5903	0.0612
2.0	550	3.5903	0.0612
2.9900	822	3.5903	0.0612

Framework versions

Transformers 4.51.2
Pytorch 2.6.0+cu126
Datasets 3.5.0
Tokenizers 0.21.1

gokulsrinivasagan/wav2vec2-base-960h-speech-commands-v1-t_70

wav2vec2-base-960h-speech-commands-v1-t_70

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

gokulsrinivasagan/
wav2vec2-base-960h-speech-commands-v1-t_70