Whisper tiny by ehzawad
This model is a fine-tuned version of
openai/whisper-tiny
on the Common Voice 13.0 dataset.
It achieves the following results on the evaluation set:
-
Loss: 0.2422
-
Wer: 75.4095
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: 16
-
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: 500
-
training_steps: 4000
-
mixed_precision_training: Native AMP
Training results
|
Training Loss
|
Epoch
|
Step
|
Validation Loss
|
Wer
|
|
0.3593
|
0.53
|
1000
|
0.3717
|
102.7311
|
|
0.2502
|
1.07
|
2000
|
0.2802
|
81.0367
|
|
0.2219
|
1.6
|
3000
|
0.2535
|
80.8361
|
|
0.2069
|
2.14
|
4000
|
0.2422
|
75.4095
|
Framework versions
-
Transformers 4.30.0.dev0
-
Pytorch 2.0.1+cu117
-
Datasets 2.12.0
-
Tokenizers 0.13.3