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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-xlsr-tamil-commonvoice |
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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-xlsr-tamil-commonvoice |
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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: 0.6145 |
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- Wer: 0.8512 |
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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: 200 |
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- num_epochs: 20 |
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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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| 12.0478 | 1.05 | 100 | 3.3867 | 1.0 | |
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| 3.2522 | 2.11 | 200 | 3.2770 | 1.0 | |
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| 3.1689 | 3.16 | 300 | 3.1135 | 1.0039 | |
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| 2.9278 | 4.21 | 400 | 2.0485 | 1.3109 | |
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| 1.3592 | 5.26 | 500 | 0.8044 | 1.0988 | |
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| 0.7472 | 6.32 | 600 | 0.6571 | 0.9474 | |
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| 0.5842 | 7.37 | 700 | 0.6079 | 0.9477 | |
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| 0.4831 | 8.42 | 800 | 0.6083 | 0.9491 | |
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| 0.4259 | 9.47 | 900 | 0.5916 | 0.8973 | |
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| 0.3817 | 10.53 | 1000 | 0.6070 | 0.9147 | |
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| 0.338 | 11.58 | 1100 | 0.5873 | 0.8617 | |
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| 0.3123 | 12.63 | 1200 | 0.5983 | 0.8844 | |
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| 0.287 | 13.68 | 1300 | 0.6146 | 0.8988 | |
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| 0.2706 | 14.74 | 1400 | 0.6068 | 0.8754 | |
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| 0.2505 | 15.79 | 1500 | 0.5996 | 0.8638 | |
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| 0.2412 | 16.84 | 1600 | 0.6106 | 0.8481 | |
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| 0.2176 | 17.89 | 1700 | 0.6152 | 0.8520 | |
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| 0.2255 | 18.95 | 1800 | 0.6150 | 0.8540 | |
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| 0.216 | 20.0 | 1900 | 0.6145 | 0.8512 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu102 |
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- Datasets 1.13.3 |
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- Tokenizers 0.10.3 |
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