scream_non_large_3e06_beams5_v2
This model is a fine-tuned version of openai/whisper-large-v2 on the NbAiLab/NCC_speech_all_v5 dataset. It achieves the following results on the evaluation set:
- step: 29999
- eval_loss: 1.2308
- train_loss: 0.2858
- eval_wer: 10.3228
- eval_cer: 5.6236
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: 3e-06
- lr_scheduler_type: linear
- per_device_train_batch_size: 5
- total_train_batch_size_per_node: 20
- total_train_batch_size: 160
- total_optimization_steps: 30,000
- starting_optimization_step: None
- finishing_optimization_step: 30,000
- num_train_dataset_workers: 32
- numb_hosts: 8
- total_num_training_examples: 4,800,000
- steps_per_epoch: 8543
- num_beams: 5
Training results
step | eval_loss | train_loss | eval_wer | eval_cer |
---|---|---|---|---|
0 | 2.0006 | 0.8864 | 15.7125 | 8.0675 |
5000 | 1.4781 | 0.3285 | 10.3532 | 5.0340 |
10000 | 1.2340 | 0.3277 | 10.8709 | 5.7596 |
15000 | 1.1556 | 0.3272 | 10.3837 | 5.3515 |
20000 | 1.2220 | 0.2775 | 10.2314 | 5.5026 |
25000 | 1.2454 | 0.2367 | 10.1705 | 5.4976 |
29999 | 1.2308 | 0.2858 | 10.3228 | 5.6236 |
Framework versions
- Transformers 4.29.0.dev0
- Datasets 2.11.0
- Tokenizers 0.13.3
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