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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 |
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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-turkish-colab |
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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 |
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type: common_voice |
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config: tr |
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split: test |
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args: tr |
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metrics: |
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- name: Wer |
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type: wer |
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value: 0.3032376672454295 |
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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-turkish-colab |
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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 dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.3896 |
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- Wer: 0.3032 |
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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: 16 |
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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: 32 |
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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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- num_epochs: 30 |
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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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| 3.9779 | 3.67 | 400 | 0.7067 | 0.7341 | |
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| 0.4349 | 7.34 | 800 | 0.4481 | 0.4499 | |
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| 0.1915 | 11.01 | 1200 | 0.4118 | 0.4095 | |
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| 0.1265 | 14.68 | 1600 | 0.3861 | 0.3772 | |
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| 0.0953 | 18.35 | 2000 | 0.4008 | 0.3560 | |
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| 0.074 | 22.02 | 2400 | 0.3965 | 0.3222 | |
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| 0.0561 | 25.69 | 2800 | 0.3853 | 0.3197 | |
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| 0.0452 | 29.36 | 3200 | 0.3896 | 0.3032 | |
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### Framework versions |
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- Transformers 4.34.0 |
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- Pytorch 2.0.1+cu118 |
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- Datasets 2.14.5 |
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- Tokenizers 0.14.1 |
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