scream_medium_beta
This model is a fine-tuned version of openai/whisper-medium on the NbAiLab/ncc_speech dataset. It achieves the following results on the evaluation set:
- step: 24999
- validation_fleurs_loss: 1.4171
- train_loss: 0.5400
- validation_fleurs_wer: 8.8638
- validation_fleurs_cer: 3.8370
- validation_fleurs_exact_wer: 14.1278
- validation_fleurs_exact_cer: 5.1993
- validation_stortinget_loss: 0.3369
- validation_stortinget_wer: 14.2120
- validation_stortinget_cer: 10.2972
- validation_stortinget_exact_wer: 17.4640
- validation_stortinget_exact_cer: 10.8352
- validation_nrk_tv_loss: 0.8259
- validation_nrk_tv_wer: 39.9035
- validation_nrk_tv_cer: 31.1762
- validation_nrk_tv_exact_wer: 47.4289
- validation_nrk_tv_exact_cer: 32.3674
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: 2.5e-05
- lr_scheduler_type: linear
- per_device_train_batch_size: 16
- total_train_batch_size_per_node: 64
- total_train_batch_size: 1024
- total_optimization_steps: 25,000
- starting_optimization_step: None
- finishing_optimization_step: 25,000
- num_train_dataset_workers: 32
- num_hosts: 16
- total_num_training_examples: 25,600,000
- steps_per_epoch: 6271
- num_beams: None
- dropout: True
- bpe_dropout_probability: 0.1
Training results
| step | validation_fleurs_loss | train_loss | validation_fleurs_wer | validation_fleurs_cer | validation_fleurs_exact_wer | validation_fleurs_exact_cer | validation_stortinget_loss | validation_stortinget_wer | validation_stortinget_cer | validation_stortinget_exact_wer | validation_stortinget_exact_cer | validation_nrk_tv_loss | validation_nrk_tv_wer | validation_nrk_tv_cer | validation_nrk_tv_exact_wer | validation_nrk_tv_exact_cer |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | 3.6595 | 2.4764 | 17.4301 | 5.4794 | 21.6249 | 6.3977 | 1.3465 | 33.9515 | 19.1377 | 38.4072 | 20.3275 | 1.8386 | 66.2133 | 48.0904 | 75.6490 | 49.8313 |
| 5000 | 1.2828 | 0.6841 | 8.8638 | 3.8864 | 13.2318 | 4.9529 | 0.3311 | 14.5798 | 10.4664 | 17.7786 | 11.0119 | 0.8229 | 41.0824 | 31.7759 | 48.7519 | 33.0088 |
| 10000 | 1.1134 | 0.6019 | 8.3284 | 3.6990 | 13.1123 | 4.9287 | 0.3132 | 14.0485 | 10.1394 | 17.2099 | 10.6785 | 0.7856 | 39.0957 | 30.3740 | 46.7798 | 31.5896 |
| 15000 | 1.1605 | 0.5821 | 8.5068 | 3.7631 | 13.5603 | 5.0157 | 0.3181 | 13.7633 | 10.0236 | 16.9465 | 10.5585 | 0.7864 | 39.4419 | 30.9142 | 46.7507 | 32.1012 |
| 20000 | 1.0986 | 0.5395 | 8.7448 | 3.9456 | 14.4863 | 5.3733 | 0.3226 | 14.2469 | 10.3402 | 17.4640 | 10.8776 | 0.7884 | 39.8129 | 31.0325 | 47.3332 | 32.2280 |
Framework versions
- Transformers 4.31.0.dev0
- Datasets 2.13.0
- Tokenizers 0.13.3
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Base model
openai/whisper-medium