metadata
library_name: transformers
language:
- sw
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_18_0
metrics:
- wer
model-index:
- name: Whisper Small Hi - Sanchit Gandhi
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_18_0
args: 'config: sw, split: test'
metrics:
- name: Wer
type: wer
value: 54.080058758722
Whisper Small Hi - Sanchit Gandhi
This model is a fine-tuned version of openai/whisper-small on the Common Voice 11.0 dataset. It achieves the following results on the evaluation set:
- Loss: 0.9542
- Wer: 54.0801
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: 5000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 0.7988 | 0.2451 | 100 | 1.2849 | 109.6915 |
| 0.8952 | 0.4902 | 200 | 1.1418 | 95.3581 |
| 0.7785 | 0.7353 | 300 | 1.0263 | 94.3665 |
| 0.7053 | 0.9804 | 400 | 0.9466 | 85.3250 |
| 0.5318 | 1.2255 | 500 | 0.9058 | 81.4873 |
| 0.4995 | 1.4706 | 600 | 0.8554 | 66.8638 |
| 0.4802 | 1.7157 | 700 | 0.8245 | 64.1645 |
| 0.4654 | 1.9608 | 800 | 0.7959 | 77.4477 |
| 0.2461 | 2.2059 | 900 | 0.8013 | 66.1440 |
| 0.2342 | 2.4510 | 1000 | 0.7986 | 52.0676 |
| 0.2239 | 2.6961 | 1100 | 0.7772 | 62.4128 |
| 0.2732 | 2.9412 | 1200 | 0.7743 | 68.8065 |
| 0.1017 | 3.1863 | 1300 | 0.8005 | 65.6739 |
| 0.1081 | 3.4314 | 1400 | 0.8069 | 68.5678 |
| 0.1045 | 3.6765 | 1500 | 0.8008 | 63.2317 |
| 0.1076 | 3.9216 | 1600 | 0.7981 | 70.0220 |
| 0.0604 | 4.1667 | 1700 | 0.8220 | 57.7194 |
| 0.0449 | 4.4118 | 1800 | 0.8294 | 68.8652 |
| 0.0488 | 4.6569 | 1900 | 0.8347 | 59.0709 |
| 0.0453 | 4.9020 | 2000 | 0.8300 | 67.5468 |
| 0.0224 | 5.1471 | 2100 | 0.8509 | 51.2523 |
| 0.0179 | 5.3922 | 2200 | 0.8573 | 59.6071 |
| 0.0224 | 5.6373 | 2300 | 0.8622 | 50.2828 |
| 0.0218 | 5.8824 | 2400 | 0.8650 | 59.3720 |
| 0.01 | 6.1275 | 2500 | 0.8657 | 74.6126 |
| 0.0109 | 6.3725 | 2600 | 0.8816 | 64.8843 |
| 0.0095 | 6.6176 | 2700 | 0.8817 | 57.7378 |
| 0.0086 | 6.8627 | 2800 | 0.8824 | 69.1223 |
| 0.0046 | 7.1078 | 2900 | 0.8988 | 58.5861 |
| 0.0037 | 7.3529 | 3000 | 0.9064 | 55.1965 |
| 0.005 | 7.5980 | 3100 | 0.9079 | 65.3654 |
| 0.0048 | 7.8431 | 3200 | 0.8993 | 52.4128 |
| 0.0023 | 8.0882 | 3300 | 0.9158 | 59.9412 |
| 0.0021 | 8.3333 | 3400 | 0.9183 | 55.7363 |
| 0.0022 | 8.5784 | 3500 | 0.9247 | 60.8336 |
| 0.002 | 8.8235 | 3600 | 0.9282 | 60.2644 |
| 0.0017 | 9.0686 | 3700 | 0.9243 | 61.2156 |
| 0.0016 | 9.3137 | 3800 | 0.9308 | 61.0797 |
| 0.0017 | 9.5588 | 3900 | 0.9399 | 52.4091 |
| 0.0014 | 9.8039 | 4000 | 0.9414 | 50.3783 |
| 0.0013 | 10.0490 | 4100 | 0.9440 | 54.8109 |
| 0.0013 | 10.2941 | 4200 | 0.9430 | 58.0353 |
| 0.0013 | 10.5392 | 4300 | 0.9472 | 55.0790 |
| 0.0012 | 10.7843 | 4400 | 0.9470 | 55.8538 |
| 0.0011 | 11.0294 | 4500 | 0.9488 | 56.8454 |
| 0.0011 | 11.2745 | 4600 | 0.9517 | 54.1315 |
| 0.0011 | 11.5196 | 4700 | 0.9530 | 53.8414 |
| 0.0011 | 11.7647 | 4800 | 0.9538 | 54.4583 |
| 0.0011 | 12.0098 | 4900 | 0.9539 | 54.0507 |
| 0.0011 | 12.2549 | 5000 | 0.9542 | 54.0801 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.1.0+cu118
- Datasets 2.21.0
- Tokenizers 0.19.1