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---
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
- generated_from_trainer
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
- bayartsogt/ulaanbal-v0
metrics:
- wer
model-index:
- name: whisper-small-mn-7-bayartsogt
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: mn
split: test
args:
language: mn
metrics:
- name: Wer
type: wer
value: 32.64693030369237
---
<!-- 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-mn-7
This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3061
- Wer: 32.6469
- Cer: 11.2319
## 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: 32
- eval_batch_size: 32
- 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: 15000
- mixed_precision_training: Native AMP
### Training script
```bash
python train.py \
--train_datasets "mozilla-foundation/common_voice_11_0|mn|train+validation,google/fleurs|mn_mn|train+validation,bayartsogt/ulaanbal-v0||train" \
--eval_datasets "mozilla-foundation/common_voice_11_0|mn|test" \
--whisper-size "small" \
--language "mn,Mongolian" \
--keep-chars " абвгдеёжзийклмноөпрстуүфхцчшъыьэюя.,?!" \
--train-batch-size 32 \
--eval-batch-size 32 \
--max-steps 15000 \
--num-workers 8 \
--version 7 \
```
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|
| 0.3416 | 0.61 | 1000 | 0.4335 | 51.0979 | 17.8608 |
| 0.2266 | 1.22 | 2000 | 0.3383 | 39.5346 | 13.6468 |
| 0.2134 | 1.83 | 3000 | 0.2994 | 35.6565 | 12.1677 |
| 0.165 | 2.43 | 4000 | 0.2927 | 34.1927 | 11.4602 |
| 0.1205 | 3.04 | 5000 | 0.2879 | 33.5209 | 11.3002 |
| 0.1284 | 3.65 | 6000 | 0.2884 | 32.7507 | 10.9885 |
| 0.0893 | 4.26 | 7000 | 0.3022 | 33.0894 | 11.2075 |
| 0.0902 | 4.87 | 8000 | 0.3061 | 32.6469 | 11.2319 |
| 0.065 | 5.48 | 9000 | 0.3233 | 32.8163 | 11.1595 |
| 0.0436 | 6.09 | 10000 | 0.3372 | 32.6852 | 11.1384 |
| 0.0469 | 6.7 | 11000 | 0.3481 | 32.8272 | 11.2867 |
| 0.0292 | 7.3 | 12000 | 0.3643 | 33.0784 | 11.3785 |
| 0.0277 | 7.91 | 13000 | 0.3700 | 33.1877 | 11.3600 |
| 0.0196 | 8.52 | 14000 | 0.3806 | 33.3734 | 11.4273 |
| 0.016 | 9.13 | 15000 | 0.3844 | 33.3188 | 11.4248 |
### Framework versions
- Transformers 4.26.0.dev0
- Pytorch 1.13.0+cu117
- Datasets 2.7.1.dev0
- Tokenizers 0.13.2
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