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--- |
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license: mit |
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base_model: facebook/w2v-bert-2.0 |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_16_0 |
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metrics: |
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- wer |
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model-index: |
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- name: w2v-bert-2.0-mongolian-colab-CV16.0-test |
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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_16_0 |
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type: common_voice_16_0 |
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config: mn |
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split: test |
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args: mn |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.872688853671421 |
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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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# w2v-bert-2.0-mongolian-colab-CV16.0-test |
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This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_16_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.5486 |
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- Wer: 0.8727 |
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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: 5e-05 |
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- train_batch_size: 4 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 16 |
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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: 100 |
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- num_epochs: 10 |
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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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| 0.7431 | 0.79 | 200 | 0.7963 | 0.9926 | |
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| 0.4379 | 1.58 | 400 | 0.6480 | 0.9805 | |
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| 0.3109 | 2.37 | 600 | 0.5584 | 0.9546 | |
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| 0.2444 | 3.17 | 800 | 0.5261 | 0.9429 | |
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| 0.2048 | 3.96 | 1000 | 0.5208 | 0.9329 | |
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| 0.1512 | 4.75 | 1200 | 0.5084 | 0.9229 | |
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| 0.1161 | 5.54 | 1400 | 0.5248 | 0.9197 | |
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| 0.0882 | 6.33 | 1600 | 0.5248 | 0.9017 | |
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| 0.0728 | 7.12 | 1800 | 0.5295 | 0.8885 | |
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| 0.0608 | 7.91 | 2000 | 0.5178 | 0.8833 | |
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| 0.0386 | 8.7 | 2200 | 0.5317 | 0.8732 | |
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| 0.0234 | 9.5 | 2400 | 0.5486 | 0.8727 | |
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### Framework versions |
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- Transformers 4.38.1 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.1 |
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- Tokenizers 0.15.2 |
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