File size: 2,162 Bytes
65669e8 a555c52 65669e8 a555c52 65669e8 a555c52 65669e8 a555c52 65669e8 a555c52 65669e8 a555c52 65669e8 cafe232 |
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 |
---
language:
- uz
license: mit
base_model: openai/whisper-large-v3-turbo
tags:
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_16_1
metrics:
- wer
model-index:
- name: Whisper Large v3 Turbo - Bahriddin Muminov
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 16.1
type: mozilla-foundation/common_voice_16_1
config: uz
split: test
args: 'config: uz, split: test'
metrics:
- name: Wer
type: wer
value: 28.258182136033867
---
<!-- 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 Large v3 Turbo - Bahriddin Muminov
This model is a fine-tuned version of [openai/whisper-large-v3-turbo](https://huggingface.co/openai/whisper-large-v3-turbo) on the Common Voice 16.1 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2958
- Wer: 28.2582
## 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: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|
| 0.429 | 0.66 | 2000 | 0.4073 | 38.0018 |
| 0.2671 | 1.32 | 4000 | 0.3378 | 31.0778 |
| 0.2511 | 1.98 | 6000 | 0.3102 | 29.2484 |
| 0.1539 | 2.64 | 8000 | 0.3022 | 30.0763 |
| 0.111 | 3.3 | 10000 | 0.2958 | 28.2582 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|