./500
This model is a fine-tuned version of openai/whisper-medium.en on the 500 SF 1000 dataset. It achieves the following results on the evaluation set:
- Loss: 0.6792
- Wer Ortho: 31.5962
- Wer: 21.0621
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-06
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- training_steps: 800
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
---|---|---|---|---|---|
1.6525 | 3.1746 | 100 | 1.1367 | 40.1968 | 29.4223 |
0.8573 | 6.3492 | 200 | 0.7964 | 30.8309 | 20.3803 |
0.6108 | 9.5238 | 300 | 0.7344 | 28.6808 | 18.9092 |
0.4957 | 12.6984 | 400 | 0.7017 | 29.1181 | 18.7298 |
0.4164 | 15.8730 | 500 | 0.6860 | 29.2274 | 18.8016 |
0.3577 | 19.0476 | 600 | 0.6802 | 29.3367 | 18.6939 |
0.3168 | 22.2222 | 700 | 0.6787 | 31.2682 | 20.7750 |
0.3023 | 25.3968 | 800 | 0.6792 | 31.5962 | 21.0621 |
Framework versions
- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
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Model tree for Makkoen/whisper-medium.en-cit-do015-wd0-lr1e-06-SF-500
Base model
openai/whisper-medium.en