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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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model-index: |
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- name: wav2vec2-large-xls-r-300m-turkish-colab_common_voice-8_4 |
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results: [] |
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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_common_voice-8_4 |
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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: 0.3201 |
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- Wer: 0.3295 |
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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: 11 |
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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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| 5.9268 | 0.51 | 400 | 1.3204 | 0.9175 | |
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| 0.7491 | 1.02 | 800 | 0.5880 | 0.6388 | |
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| 0.4911 | 1.53 | 1200 | 0.4680 | 0.5613 | |
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| 0.4265 | 2.04 | 1600 | 0.4213 | 0.5059 | |
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| 0.3473 | 2.55 | 2000 | 0.4199 | 0.4955 | |
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| 0.3291 | 3.07 | 2400 | 0.4323 | 0.5061 | |
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| 0.2819 | 3.58 | 2800 | 0.4026 | 0.4490 | |
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| 0.2628 | 4.09 | 3200 | 0.3831 | 0.4446 | |
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| 0.2371 | 4.6 | 3600 | 0.3622 | 0.4234 | |
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| 0.2274 | 5.11 | 4000 | 0.3473 | 0.4012 | |
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| 0.2051 | 5.62 | 4400 | 0.3471 | 0.3998 | |
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| 0.1985 | 6.13 | 4800 | 0.3759 | 0.4088 | |
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| 0.1767 | 6.64 | 5200 | 0.3620 | 0.4012 | |
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| 0.1707 | 7.15 | 5600 | 0.3415 | 0.3700 | |
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| 0.1559 | 7.66 | 6000 | 0.3317 | 0.3661 | |
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| 0.147 | 8.17 | 6400 | 0.3265 | 0.3618 | |
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| 0.1339 | 8.68 | 6800 | 0.3293 | 0.3586 | |
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| 0.126 | 9.2 | 7200 | 0.3386 | 0.3458 | |
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| 0.1149 | 9.71 | 7600 | 0.3305 | 0.3397 | |
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| 0.1051 | 10.22 | 8000 | 0.3235 | 0.3354 | |
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| 0.1005 | 10.73 | 8400 | 0.3201 | 0.3295 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu113 |
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- Datasets 2.1.0 |
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- Tokenizers 0.10.3 |
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