metadata
license: apache-2.0
base_model: openai/whisper-tiny.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisperFinetuneFinal
results: []
whisperFinetuneFinal
This model is a fine-tuned version of openai/whisper-tiny.en on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5711
- Wer: 22.2920
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: 0.001
- train_batch_size: 128
- 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: 100
Training results
Training Loss | Epoch | Step | Validation Loss | Wer |
---|---|---|---|---|
2.8037 | 0.2778 | 10 | 1.8972 | 34.0973 |
0.8101 | 0.5556 | 20 | 0.6863 | 28.6970 |
0.5778 | 0.8333 | 30 | 0.5491 | 22.8885 |
0.4375 | 1.1111 | 40 | 0.4962 | 20.7535 |
0.3437 | 1.3889 | 50 | 0.4767 | 20.2512 |
0.3277 | 1.6667 | 60 | 0.4921 | 21.0047 |
0.3431 | 1.9444 | 70 | 0.4972 | 20.4082 |
0.1331 | 2.2222 | 80 | 0.5317 | 25.7143 |
0.1385 | 2.5 | 90 | 0.5308 | 20.4396 |
0.146 | 2.7778 | 100 | 0.5711 | 22.2920 |
Framework versions
- Transformers 4.40.1
- Pytorch 2.2.1+cu121
- Datasets 2.19.1.dev0
- Tokenizers 0.19.1