File size: 2,540 Bytes
b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b b62b780 302b45b |
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 |
---
library_name: transformers
language:
- uz
license: apache-2.0
base_model: openai/whisper-small
tags:
- generated_from_trainer
- automatic-speech-recognition
- whisper
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: Whisper Small Uzbek
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17.0
type: mozilla-foundation/common_voice_17_0
args: 'config: uz, split: test'
metrics:
- type: wer
value: 35.8660
name: Wer
---
<!-- 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. -->
# Whisper Small Uzbek
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the Common Voice 17.0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3776
- Wer: 35.8660
## 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: 2e-05
- 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: linear
- lr_scheduler_warmup_steps: 1500
- training_steps: 5500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.913 | 0.2 | 500 | 0.8213 | 62.5843 |
| 0.6404 | 0.4 | 1000 | 0.6082 | 51.8716 |
| 0.5734 | 0.6 | 1500 | 0.5458 | 48.0513 |
| 0.5051 | 0.8 | 2000 | 0.4846 | 43.8649 |
| 0.4407 | 1.0 | 2500 | 0.4483 | 41.3901 |
| 0.3436 | 1.2 | 3000 | 0.4321 | 41.0277 |
| 0.3092 | 1.4 | 3500 | 0.4184 | 40.1141 |
| 0.2861 | 1.6 | 4000 | 0.4091 | 39.9753 |
| 0.289 | 1.8 | 4500 | 0.3811 | 36.7950 |
| 0.2816 | 2.0 | 5000 | 0.3730 | 36.7102 |
| 0.1547 | 2.2 | 5500 | 0.3776 | 35.8660 |
### Framework versions
- Transformers 4.47.0
- Pytorch 2.1.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0
|