File size: 2,283 Bytes
61aec64 6eed8a9 61aec64 6e95907 61aec64 |
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 |
---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-tiny
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: kyrgyz_asr
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: ky
split: None
args: ky
metrics:
- name: Wer
type: wer
value: 38.50746268656716
---
<!-- 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. -->
# kyrgyz_asr
This model is a fine-tuned version of [openai/whisper-tiny](https://huggingface.co./openai/whisper-tiny) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3324
- Wer: 38.5075
## Model description
This is a test fine-tuning of Whisper Tiny for the Kyrgyz language using a dataset from the Mozilla Foundation. The code is taken from [this source](https://astanahub.com/en/blog/obuchaem-whisper-small-dlia-raspoznavaniia-kazakhskoi-rechi).
## Intended uses & limitations
More information needed
## Training and evaluation data
mozilla-foundation/common_voice_17_0 (ky - kyrgyz)
## 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: Use OptimizerNames.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: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 0.59 | 0.4735 | 1000 | 0.5917 | 60.8051 |
| 0.4987 | 0.9470 | 2000 | 0.4195 | 47.8517 |
| 0.3932 | 1.4205 | 3000 | 0.3561 | 42.6685 |
| 0.3441 | 1.8939 | 4000 | 0.3324 | 38.5075 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.5.1+cu124
- Datasets 3.3.2
- Tokenizers 0.21.0
|