Whisper tiny LB - AKABI
This model is a fine-tuned version of openai/whisper-tiny on the google/fleurs dataset. It achieves the following results on the evaluation set:
- Loss: 1.4215
- Wer Ortho: 62.8649
- Wer: 60.1867
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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- training_steps: 4000
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|---|---|---|---|---|---|
| 0.9979 | 1.37 | 250 | 1.5394 | 73.1448 | 73.3298 |
| 0.6784 | 2.75 | 500 | 1.2998 | 66.9095 | 64.8060 |
| 0.3773 | 4.12 | 750 | 1.2317 | 63.9250 | 61.5385 |
| 0.2906 | 5.49 | 1000 | 1.2117 | 63.0759 | 60.3958 |
| 0.2052 | 6.87 | 1250 | 1.2157 | 64.1913 | 62.0685 |
| 0.1155 | 8.24 | 1500 | 1.2432 | 61.6791 | 59.6130 |
| 0.0912 | 9.62 | 1750 | 1.2684 | 63.0056 | 60.3229 |
| 0.0698 | 10.99 | 2000 | 1.2937 | 63.6788 | 60.9598 |
| 0.0396 | 12.36 | 2250 | 1.3224 | 62.7996 | 60.2451 |
| 0.0309 | 13.74 | 2500 | 1.3480 | 62.1514 | 59.4622 |
| 0.0205 | 15.11 | 2750 | 1.3696 | 62.1715 | 59.5303 |
| 0.017 | 16.48 | 3000 | 1.3895 | 62.0761 | 59.8074 |
| 0.0151 | 17.86 | 3250 | 1.4016 | 62.7745 | 60.0360 |
| 0.0125 | 19.23 | 3500 | 1.4126 | 62.8900 | 60.5952 |
| 0.012 | 20.6 | 3750 | 1.4202 | 63.0709 | 60.3909 |
| 0.0115 | 21.98 | 4000 | 1.4215 | 62.8649 | 60.1867 |
Framework versions
- Transformers 4.32.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3
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