metadata

license: apache-2.0
base_model: openai/whisper-large-v2
tags:
  - generated_from_trainer
datasets:
  - common_voice_17_0
model-index:
  - name: whisper-large-v2-finetuning
    results: []

whisper-large-v2-finetuning

This model is a fine-tuned version of openai/whisper-large-v2 on the common_voice_17_0 dataset. It achieves the following results on the evaluation set:

eval_loss: 0.1803
eval_wer: 14.9238
eval_runtime: 3860.013
eval_samples_per_second: 2.453
eval_steps_per_second: 0.307
epoch: 1.5267
step: 3000

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: 8000
mixed_precision_training: Native AMP

Framework versions

Transformers 4.42.3
Pytorch 2.2.1
Datasets 2.20.0
Tokenizers 0.19.1