File size: 3,366 Bytes
786a785 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 |
---
library_name: transformers
language:
- sw
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: stt-april-1
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 17
type: mozilla-foundation/common_voice_17_0
metrics:
- name: Wer
type: wer
value: 26.149347116430903
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# stt-april-1
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7422
- Wer Ortho: 32.1876
- Wer: 26.1493
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: constant_with_warmup
- lr_scheduler_warmup_steps: 50
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer |
|:-------------:|:-------:|:-----:|:---------------:|:---------:|:-------:|
| 0.6457 | 0.6180 | 500 | 0.6308 | 38.7728 | 31.6649 |
| 0.3566 | 1.2361 | 1000 | 0.5699 | 36.3837 | 29.0941 |
| 0.3687 | 1.8541 | 1500 | 0.5554 | 34.7230 | 27.5095 |
| 0.2412 | 2.4722 | 2000 | 0.5469 | 31.7690 | 25.0986 |
| 0.1654 | 3.0902 | 2500 | 0.6037 | 32.8070 | 26.1459 |
| 0.172 | 3.7083 | 3000 | 0.5907 | 32.5790 | 25.2142 |
| 0.1214 | 4.3263 | 3500 | 0.6065 | 31.8337 | 24.9354 |
| 0.1488 | 4.9444 | 4000 | 0.6024 | 31.5376 | 24.9966 |
| 0.1034 | 5.5624 | 4500 | 0.6288 | 32.1161 | 25.4931 |
| 0.0818 | 6.1805 | 5000 | 0.6470 | 31.9051 | 25.5373 |
| 0.0955 | 6.7985 | 5500 | 0.6566 | 32.1195 | 25.4795 |
| 0.0744 | 7.4166 | 6000 | 0.6748 | 31.9153 | 25.6257 |
| 0.0784 | 8.0346 | 6500 | 0.6908 | 32.3577 | 25.9759 |
| 0.0684 | 8.6527 | 7000 | 0.6959 | 32.6538 | 26.3772 |
| 0.0587 | 9.2707 | 7500 | 0.7318 | 32.2931 | 25.7991 |
| 0.0656 | 9.8888 | 8000 | 0.7182 | 32.1467 | 25.8535 |
| 0.0589 | 10.5068 | 8500 | 0.7361 | 32.4428 | 26.3500 |
| 0.049 | 11.1248 | 9000 | 0.7597 | 32.3884 | 25.9827 |
| 0.0562 | 11.7429 | 9500 | 0.7504 | 32.2318 | 25.7481 |
| 0.0503 | 12.3609 | 10000 | 0.7422 | 32.1876 | 26.1493 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0
|