This model is a fine-tuned version of distil-whisper/distil-medium.en on the Speech Commands dataset. It achieves the following results on the evaluation set:

Loss: 1.6851
Accuracy: 0.8067

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: 8
eval_batch_size: 8
seed: 42
distributed_type: multi-GPU
num_devices: 4
total_train_batch_size: 32
total_eval_batch_size: 32
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: 10
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Accuracy
0.1179	1.0	1236	0.8986	0.7990
0.1177	2.0	2472	0.8863	0.8008
0.0953	3.0	3708	0.9958	0.8031
0.1288	4.0	4944	1.0659	0.8017
0.0575	5.0	6180	1.1709	0.8026
0.0011	6.0	7416	1.1123	0.8049
0.0005	7.0	8652	1.2285	0.8049
0.0006	8.0	9888	1.3904	0.8058
0.001	9.0	11124	1.4603	0.8067
0.0001	10.0	12360	1.6851	0.8067

Framework versions

Transformers 4.46.3
Pytorch 2.4.1+cu121
Datasets 3.1.0
Tokenizers 0.20.3

world-of-june/distil-medium.en-ft-kws-speech-commands

distil-medium.en-ft-kws-speech-commands

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

world-of-june/
distil-medium.en-ft-kws-speech-commands