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---
language: mn
license: apache-2.0
tags:
- whisper-event
- hf-asr-leaderboard
- generated_from_multiple_datasets
datasets:
- mozilla-foundation/common_voice_11_0
- google/fleurs
- bayartsogt/ulaanbal-v0
- bayartsogt/youtube-mongolian-v1
metrics:
- wer
- cer
model-index:
- name: whisper-medium-mn-10
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 11.0
type: mozilla-foundation/common_voice_11_0
config: mn
split: test
metrics:
- type: wer
value: 21.258466244264802
name: Wer
- type: cer
value: 6.875610660018193
name: Cer
---
<!-- 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-medium-mn-10
This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2103
- Wer: 21.2585
- Cer: 6.8756
## 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: 8
- 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: 500
- training_steps: 40000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Cer | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:-------:|:---------------:|:-------:|
| 0.4197 | 0.09 | 1000 | 19.0947 | 0.4462 | 53.9600 |
| 0.3288 | 0.17 | 2000 | 14.8016 | 0.3468 | 44.2102 |
| 0.2737 | 0.26 | 3000 | 12.3471 | 0.3020 | 36.1700 |
| 0.2558 | 0.35 | 4000 | 11.7171 | 0.2824 | 34.1709 |
| 0.2406 | 0.43 | 5000 | 10.3551 | 0.2594 | 31.1230 |
| 0.218 | 0.52 | 6000 | 9.7815 | 0.2452 | 29.6865 |
| 0.2253 | 0.61 | 7000 | 9.6712 | 0.2344 | 29.2932 |
| 0.2071 | 0.69 | 8000 | 9.4261 | 0.2283 | 28.5067 |
| 0.2051 | 0.78 | 9000 | 9.0656 | 0.2224 | 27.4033 |
| 0.2064 | 0.87 | 10000 | 8.7851 | 0.2138 | 26.7206 |
| 0.193 | 0.95 | 11000 | 8.5021 | 0.2089 | 25.5790 |
| 0.1577 | 1.04 | 12000 | 8.2873 | 0.2072 | 25.6118 |
| 0.1397 | 1.13 | 13000 | 8.2368 | 0.2046 | 25.1147 |
| 0.1526 | 1.21 | 14000 | 8.7615 | 0.2065 | 26.4638 |
| 0.1497 | 1.3 | 15000 | 0.2004 | 24.4866 | 7.9588 |
| 0.1569 | 1.39 | 16000 | 0.1990 | 24.2244 | 7.9554 |
| 0.1416 | 1.47 | 17000 | 0.2001 | 24.2298 | 7.8754 |
| 0.1371 | 1.56 | 18000 | 0.1932 | 23.6072 | 7.8072 |
| 0.1379 | 1.65 | 19000 | 0.1916 | 23.1320 | 7.5452 |
| 0.1305 | 1.73 | 20000 | 0.1880 | 23.1101 | 7.4290 |
| 0.1395 | 1.82 | 21000 | 0.1877 | 22.9845 | 7.4635 |
| 0.1418 | 1.91 | 22000 | 0.1862 | 22.9080 | 7.5907 |
| 0.1432 | 1.99 | 23000 | 0.1847 | 22.7114 | 7.4290 |
| 0.0965 | 2.08 | 24000 | 0.1931 | 21.7391 | 7.0399 |
| 0.0723 | 2.17 | 25000 | 0.1961 | 22.3236 | 7.2698 |
| 0.0773 | 2.25 | 26000 | 0.1977 | 22.0505 | 7.0752 |
| 0.0862 | 2.34 | 27000 | 0.1959 | 21.9522 | 7.0820 |
| 0.0739 | 2.43 | 28000 | 0.1982 | 21.7719 | 7.1494 |
| 0.0843 | 2.51 | 29000 | 0.1963 | 21.8921 | 7.1241 |
| 0.0734 | 2.6 | 30000 | 0.1980 | 21.7883 | 7.1317 |
| 0.0785 | 2.69 | 31000 | 0.1955 | 21.8757 | 7.1948 |
| 0.0691 | 2.77 | 32000 | 0.1978 | 21.7446 | 7.0938 |
| 0.0834 | 2.86 | 33000 | 0.1953 | 21.3240 | 7.0121 |
| 0.0675 | 2.95 | 34000 | 0.1958 | 21.7719 | 7.0769 |
| 0.042 | 3.03 | 35000 | 0.2053 | 21.3404 | 6.9624 |
| 0.0474 | 3.12 | 36000 | 0.2097 | 21.5534 | 7.0306 |
| 0.0428 | 3.21 | 37000 | 0.2107 | 21.3185 | 6.9809 |
| 0.0343 | 3.29 | 38000 | 0.2111 | 21.3896 | 6.9514 |
| 0.0378 | 3.38 | 39000 | 0.2103 | 21.2585 | 6.8756 |
| 0.0361 | 3.47 | 40000 | 0.2106 | 21.3677 | 6.9009 |
### 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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