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--- |
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base_model: ylacombe/w2v-bert-2.0-600m-turkish-colab |
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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: mactest2 |
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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: 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: 0.3088954056695992 |
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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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# mactest2 |
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This model is a fine-tuned version of [ylacombe/w2v-bert-2.0-600m-turkish-colab](https://huggingface.co/ylacombe/w2v-bert-2.0-600m-turkish-colab) 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: 0.5663 |
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- Wer: 0.3089 |
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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: 8 |
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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: 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: 150 |
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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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| 0.305 | 1.6 | 100 | 0.4562 | 0.2952 | |
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| 0.0505 | 3.2 | 200 | 0.4923 | 0.3284 | |
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| 0.0298 | 4.8 | 300 | 0.4925 | 0.3157 | |
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| 0.0156 | 6.4 | 400 | 0.5194 | 0.3069 | |
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| 0.0058 | 8.0 | 500 | 0.5420 | 0.3050 | |
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| 0.004 | 9.6 | 600 | 0.5663 | 0.3089 | |
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### Framework versions |
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- Transformers 4.37.0.dev0 |
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- Pytorch 2.1.0+cu121 |
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- Datasets 2.16.1 |
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- Tokenizers 0.15.0 |
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