TMP prvontni trenovani jazyk en, train en de en similar
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: 0.3401
- Wer: 17.3873
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 |
|---|---|---|---|---|
| 0.0979 | 1.12 | 500 | 0.2481 | 19.0875 |
| 0.0097 | 3.12 | 1000 | 0.2917 | 16.7763 |
| 0.0017 | 5.12 | 1500 | 0.3298 | 16.9689 |
| 0.0011 | 7.12 | 2000 | 0.3401 | 17.3873 |
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-medium-lang_en-set-en-de-en_similar
Base model
openai/whisper-mediumDataset used to train xbilek25/w-medium-lang_en-set-en-de-en_similar
Evaluation results
- Wer on xbilek25/train_set_1st_1000_de_en_deself-reported17.387