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Sania67/
Fine_tune_whisper_small

Name: Fine_tune_whisper_small
Availability: InStock

automatic-speech-recognition

generated_from_trainer

apache-2.0

endpoints_compatible

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Fine_tune_whisper_small

This model is a fine-tuned version of openai/whisper-small on our own recorded dataset (700 audio samples). It achieves the following results on the evaluation set:

Loss: 0.8225
Wer: 43.7477

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: 200
training_steps: 900
mixed_precision_training: Native AMP

Training results

Training Loss	Epoch	Step	Validation Loss	Wer
0.2991	3.92	200	0.6605	44.1903
0.0185	7.84	400	0.7377	42.8624
0.0026	11.76	600	0.8087	43.0837
0.0011	15.69	800	0.8225	43.7477

Framework versions

Transformers 4.25.0.dev0
Pytorch 1.12.1+cu113
Datasets 2.7.1
Tokenizers 0.13.2

Sania67/Fine_tune_whisper_small

Fine_tune_whisper_small

Model description

Intended uses & limitations

Training and evaluation data

Training procedure

Training hyperparameters

Training results

Framework versions

Sania67/
Fine_tune_whisper_small