metadata

language:
  - he
license: apache-2.0
base_model: openai/whisper-medium
tags:
  - generated_from_trainer
metrics:
  - wer
model-index:
  - name: whisper-medium-he
    results: []

whisper-medium-he

This model is a fine-tuned version of openai/whisper-medium on the imvladikon/hebrew_speech_coursera dataset. It achieves the following results on the evaluation set:

Loss: 0.2042
Wer: 12.9071

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: 1
eval_batch_size: 1
seed: 42
gradient_accumulation_steps: 2
total_train_batch_size: 2
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
0.1865	0.1	1000	0.3587	21.4973
0.2601	0.2	2000	0.2673	17.1157
0.2033	0.3	3000	0.2238	14.4325
0.1988	0.39	4000	0.2042	12.9071

Framework versions

Transformers 4.36.0.dev0
Pytorch 2.1.0+cu118
Datasets 2.15.0
Tokenizers 0.15.0