model trenovan na en de en similar setu, nastaveni jazyka de
This model is a fine-tuned version of openai/whisper-medium on the xbilek25/train_set_1st_1000_de_en_de dataset. It achieves the following results on the evaluation set:
- Loss: 0.3156
- Wer: 18.2905
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: 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: 1
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0119 | 3.12 | 1000 | 0.2831 | 20.0106 |
| 0.0015 | 7.12 | 2000 | 0.3156 | 18.2905 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
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Model tree for xbilek25/w-m-lang_de-set_en-de-en_similar
Base model
openai/whisper-mediumDataset used to train xbilek25/w-m-lang_de-set_en-de-en_similar
Evaluation results
- Wer on xbilek25/train_set_1st_1000_de_en_deself-reported18.290