nicekevin/whisper_bs_ft_lgevr2_v3_2
This model is a fine-tuned version of openai/whisper-base on the lgevr_sentence_v2 dataset. It achieves the following results on the evaluation set:
- eval_loss: 0.4283
- eval_cer: 12.9976
- eval_runtime: 10.4189
- eval_samples_per_second: 3.743
- eval_steps_per_second: 0.48
- epoch: 25.0
- step: 500
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: 2e-06
- 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: 2000
- mixed_precision_training: Native AMP
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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Base model
openai/whisper-base