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README.md
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---
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language:
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- tr
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- common_voice
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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-common_voice-tr-demo
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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-common_voice-tr-demo
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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 - TR dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3815
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- Wer: 0.3493
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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: 15.0
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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 | 0.92 | 100 | 3.5559 | 1.0 |
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| No log | 1.83 | 200 | 3.0161 | 0.9999 |
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| No log | 2.75 | 300 | 0.8587 | 0.7443 |
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| No log | 3.67 | 400 | 0.5855 | 0.6121 |
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| 3.1095 | 4.59 | 500 | 0.4841 | 0.5204 |
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| 3.1095 | 5.5 | 600 | 0.4533 | 0.4923 |
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| 3.1095 | 6.42 | 700 | 0.4157 | 0.4342 |
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| 3.1095 | 7.34 | 800 | 0.4304 | 0.4334 |
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| 3.1095 | 8.26 | 900 | 0.4097 | 0.4068 |
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| 0.2249 | 9.17 | 1000 | 0.4049 | 0.3881 |
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| 0.2249 | 10.09 | 1100 | 0.3993 | 0.3809 |
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| 0.2249 | 11.01 | 1200 | 0.3855 | 0.3782 |
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| 0.2249 | 11.93 | 1300 | 0.3923 | 0.3713 |
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| 0.2249 | 12.84 | 1400 | 0.3833 | 0.3591 |
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| 0.1029 | 13.76 | 1500 | 0.3811 | 0.3570 |
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| 0.1029 | 14.68 | 1600 | 0.3834 | 0.3499 |
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### Framework versions
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- Transformers 4.13.0.dev0
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- Pytorch 1.12.0a0+2c916ef
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- Datasets 2.2.2
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- Tokenizers 0.10.3
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