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--- |
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license: apache-2.0 |
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tags: |
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- whisper-event |
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- hf-asr-leaderboard |
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- generated_from_trainer |
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datasets: |
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- mozilla-foundation/common_voice_11_0 |
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- google/fleurs |
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- bayartsogt/ulaanbal-v0 |
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- bayartsogt/youtube-mongolian-v1 |
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metrics: |
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- wer |
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- cer |
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model-index: |
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- name: whisper-small-mn-8-bayartsogt |
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results: |
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- task: |
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name: Automatic Speech Recognition |
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type: automatic-speech-recognition |
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dataset: |
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name: Common Voice 11.0 |
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type: mozilla-foundation/common_voice_11_0 |
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config: mn |
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split: test |
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args: |
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language: mn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 26.518461874590344 |
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- name: Cer |
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type: cer |
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value: 9.46811616603981 |
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--- |
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
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should probably proofread and complete it, then remove this comment. --> |
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# whisper-small-mn-8 |
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This model is a fine-tuned version of [openai/whisper-small](https://huggingface.co/openai/whisper-small) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.2421 |
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- Wer: 26.5185 |
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- Cer: 9.4681 |
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## Model description |
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More information needed |
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## Intended uses & limitations |
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More information needed |
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## Training and evaluation data |
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More information needed |
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## Training procedure |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 1e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- lr_scheduler_warmup_steps: 500 |
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- training_steps: 15000 |
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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
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|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:| |
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| 0.3717 | 0.35 | 1000 | 0.4004 | 46.9576 | 16.9664 | |
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| 0.286 | 0.69 | 2000 | 0.3129 | 37.3935 | 13.5504 | |
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| 0.2287 | 1.04 | 3000 | 0.2768 | 33.1931 | 11.7806 | |
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| 0.2257 | 1.39 | 4000 | 0.2590 | 30.7243 | 11.0232 | |
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| 0.2029 | 1.73 | 5000 | 0.2428 | 29.2003 | 10.4144 | |
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| 0.1691 | 2.08 | 6000 | 0.2408 | 28.4357 | 10.0306 | |
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| 0.1626 | 2.43 | 7000 | 0.2369 | 28.0588 | 10.0486 | |
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| 0.1588 | 2.77 | 8000 | 0.2321 | 27.2340 | 9.6819 | |
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| 0.1271 | 3.12 | 9000 | 0.2349 | 26.8407 | 9.5574 | |
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| 0.1263 | 3.47 | 10000 | 0.2356 | 27.1630 | 9.6519 | |
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| 0.1314 | 3.81 | 11000 | 0.2340 | 26.5567 | 9.4278 | |
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| 0.1062 | 4.16 | 12000 | 0.2390 | 26.6332 | 9.5162 | |
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| 0.1081 | 4.5 | 13000 | 0.2398 | 26.5840 | 9.5085 | |
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| 0.1033 | 4.85 | 14000 | 0.2402 | 26.7096 | 9.4801 | |
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| 0.097 | 5.2 | 15000 | 0.2421 | 26.5185 | 9.4681 | |
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### Framework versions |
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- Transformers 4.26.0.dev0 |
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- Pytorch 1.13.0+cu117 |
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- Datasets 2.7.1.dev0 |
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- Tokenizers 0.13.2 |
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