basic_train_basic_test 1000 similar params: per_device_train_batch_size=32, # bylo 16 a pod tim 1 gradient_accumulation_steps=2, warmup_steps=300, max_steps=3000
This model is a fine-tuned version of openai/whisper-small on the xbilek25/train_set_1st_1000_de_en_de dataset. It achieves the following results on the evaluation set:
- Loss: 0.6605
- Wer: 25.4637
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: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.0072 | 9.01 | 600 | 0.5727 | 22.6644 |
| 0.0009 | 19.0 | 1200 | 0.6166 | 23.9460 |
| 0.0006 | 28.01 | 1800 | 0.6416 | 24.7892 |
| 0.0004 | 38.0 | 2400 | 0.6551 | 25.2951 |
| 0.0004 | 47.01 | 3000 | 0.6605 | 25.4637 |
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/whisper-small-train-v3.0
Base model
openai/whisper-smallDataset used to train xbilek25/whisper-small-train-v3.0
Evaluation results
- Wer on xbilek25/train_set_1st_1000_de_en_deself-reported25.464