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Whisper Small Sv - Riksdag 100h
This model is a fine-tuned version of openai/whisper-small on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4977
- Wer: 1118.4718
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-05
- train_batch_size: 8
- 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: 20000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.1384 | 0.11 | 1000 | 0.4747 | 380.8335 |
0.1186 | 0.22 | 2000 | 0.4513 | 1032.3900 |
0.1056 | 0.33 | 3000 | 0.4385 | 582.0427 |
0.0824 | 0.43 | 4000 | 0.4465 | 574.8907 |
0.0961 | 0.54 | 5000 | 0.4199 | 1004.9138 |
0.0939 | 0.65 | 6000 | 0.4478 | 866.2979 |
0.0758 | 0.76 | 7000 | 0.4384 | 907.9496 |
0.0741 | 0.87 | 8000 | 0.4264 | 641.1371 |
0.0692 | 0.98 | 9000 | 0.4206 | 1142.6550 |
0.0257 | 1.08 | 10000 | 0.4707 | 1152.4312 |
0.0273 | 1.19 | 11000 | 0.4789 | 1100.2058 |
0.021 | 1.3 | 12000 | 0.4763 | 1236.1719 |
0.0163 | 1.41 | 13000 | 0.5035 | 924.8006 |
0.0183 | 1.52 | 14000 | 0.4911 | 1285.1814 |
0.024 | 1.63 | 15000 | 0.4861 | 1140.8284 |
0.0158 | 1.73 | 16000 | 0.4793 | 1181.7597 |
0.0167 | 1.84 | 17000 | 0.4759 | 1207.3064 |
0.0231 | 1.95 | 18000 | 0.4801 | 1139.6964 |
0.0054 | 2.06 | 19000 | 0.4934 | 1114.4842 |
0.006 | 2.17 | 20000 | 0.4977 | 1118.4718 |
Framework versions
- Transformers 4.27.0.dev0
- Pytorch 1.13.1
- Datasets 2.10.1
- Tokenizers 0.13.2