Whisper Medium Fi - Teemu Sormunen
This model is a fine-tuned version of openai/whisper-medium on the Common Voice 11.0, train+val dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.2453
- eval_wer: 16.3871
- eval_runtime: 1296.4339
- eval_samples_per_second: 1.314
- eval_steps_per_second: 0.164
- epoch: 5.04
- step: 300
Model description
Checkpoint of a Finnish model trained with Common Voice 11.0 train+validation data. The data is very small, and already during 300 steps the model overfit on training data.
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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 1000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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