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--- |
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language: |
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- mn |
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license: apache-2.0 |
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tags: |
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- automatic-speech-recognition |
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- mozilla-foundation/common_voice_7_0 |
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- generated_from_trainer |
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- mn |
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- robust-speech-event |
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- model_for_talk |
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datasets: |
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- common_voice |
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model-index: |
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- name: XLS-R-300M - Mongolian |
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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 7 |
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type: mozilla-foundation/common_voice_7_0 |
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args: mn |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 44.709 |
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- name: Test CER |
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type: cer |
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value: 13.532 |
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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: Robust Speech Event - Dev Data |
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type: speech-recognition-community-v2/dev_data |
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args: mn |
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metrics: |
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- name: Test WER |
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type: wer |
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value: 76.643 |
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- name: Test CER |
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type: cer |
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value: 36.997 |
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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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# wav2vec2-large-xls-r-300m-mongolian |
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_7_0 - MN dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6003 |
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- Wer: 0.4473 |
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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: 0.0003 |
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- train_batch_size: 32 |
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- eval_batch_size: 1 |
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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: 2000 |
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- num_epochs: 100.0 |
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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 | |
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|:-------------:|:-----:|:-----:|:---------------:|:------:| |
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| 1.3677 | 15.87 | 2000 | 0.6432 | 0.6198 | |
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| 1.1379 | 31.75 | 4000 | 0.6196 | 0.5592 | |
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| 1.0093 | 47.62 | 6000 | 0.5828 | 0.5117 | |
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| 0.8888 | 63.49 | 8000 | 0.5754 | 0.4822 | |
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| 0.7985 | 79.37 | 10000 | 0.5987 | 0.4690 | |
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| 0.697 | 95.24 | 12000 | 0.6014 | 0.4471 | |
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### Framework versions |
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- Transformers 4.16.0.dev0 |
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- Pytorch 1.10.1+cu102 |
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- Datasets 1.17.1.dev0 |
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- Tokenizers 0.11.0 |
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