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--- |
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license: apache-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 |
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metrics: |
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- wer |
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model-index: |
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- name: wav2vec2-large-xlsr-turkish-demo-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: 0.4821775099581248 |
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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-xlsr-turkish-demo-colab |
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This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4151 |
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- Wer: 0.4822 |
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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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- 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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| 5.2487 | 4.26 | 400 | 1.6455 | 1.0778 | |
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| 0.71 | 8.51 | 800 | 0.4428 | 0.6138 | |
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| 0.3073 | 12.77 | 1200 | 0.4214 | 0.5517 | |
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| 0.2136 | 17.02 | 1600 | 0.4345 | 0.5193 | |
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| 0.1624 | 21.28 | 2000 | 0.4366 | 0.5026 | |
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| 0.1298 | 25.53 | 2400 | 0.4111 | 0.4949 | |
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| 0.1174 | 29.79 | 2800 | 0.4151 | 0.4822 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.10.1 |
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- Tokenizers 0.13.2 |
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