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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-xls-r-300m |
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tags: |
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- generated_from_trainer |
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datasets: |
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- common_voice_17_0 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xls-r-300m-saha-yakut |
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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_17_0 |
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type: common_voice_17_0 |
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config: sah |
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split: test |
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args: sah |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.5216510903426791 |
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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-saha-yakut |
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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 common_voice_17_0 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6404 |
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- Wer: 0.5217 |
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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: 0.0002 |
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- train_batch_size: 12 |
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- eval_batch_size: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 2 |
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- total_train_batch_size: 24 |
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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: 250 |
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- num_epochs: 30 |
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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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| No log | 3.4483 | 150 | 3.1675 | 1.0 | |
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| No log | 6.8966 | 300 | 1.1392 | 0.8509 | |
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| 3.5746 | 10.3448 | 450 | 0.6103 | 0.5812 | |
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| 3.5746 | 13.7931 | 600 | 0.6152 | 0.5565 | |
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| 3.5746 | 17.2414 | 750 | 0.6420 | 0.5382 | |
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| 0.2138 | 20.6897 | 900 | 0.6344 | 0.5245 | |
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| 0.2138 | 24.1379 | 1050 | 0.6543 | 0.5303 | |
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| 0.1148 | 27.5862 | 1200 | 0.6404 | 0.5217 | |
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### Framework versions |
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- Transformers 4.41.0.dev0 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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