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/basic_train_set_en_last3cs_1000 dataset. It achieves the following results on the evaluation set:
- Loss: 0.3732
- Wer: 29.7470
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: 200
- training_steps: 2000
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
0.0021 | 7.03 | 500 | 0.3407 | 32.9174 |
0.0008 | 15.03 | 1000 | 0.3548 | 27.6897 |
0.0005 | 23.03 | 1500 | 0.3684 | 30.3204 |
0.0004 | 31.02 | 2000 | 0.3732 | 29.7470 |
Framework versions
- Transformers 4.37.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.15.2
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Finetuned from
Dataset used to train xbilek25/whisper-small-train-v2.0
Evaluation results
- Wer on xbilek25/basic_train_set_en_last3cs_1000self-reported29.747