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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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model-index: |
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- name: wav2vec2-large-xlsr-53_toy_train_data_augment_0.1 |
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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-53_toy_train_data_augment_0.1 |
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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 None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.4658 |
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- Wer: 0.5037 |
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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: 0.0001 |
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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: 1000 |
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- num_epochs: 20 |
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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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| 3.447 | 1.05 | 250 | 3.3799 | 1.0 | |
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| 3.089 | 2.1 | 500 | 3.4868 | 1.0 | |
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| 3.063 | 3.15 | 750 | 3.3155 | 1.0 | |
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| 2.4008 | 4.2 | 1000 | 1.2934 | 0.8919 | |
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| 1.618 | 5.25 | 1250 | 0.7847 | 0.7338 | |
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| 1.3038 | 6.3 | 1500 | 0.6459 | 0.6712 | |
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| 1.2074 | 7.35 | 1750 | 0.5705 | 0.6269 | |
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| 1.1062 | 8.4 | 2000 | 0.5267 | 0.5843 | |
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| 1.026 | 9.45 | 2250 | 0.5108 | 0.5683 | |
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| 0.9505 | 10.5 | 2500 | 0.5066 | 0.5568 | |
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| 0.893 | 11.55 | 2750 | 0.5161 | 0.5532 | |
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| 0.8535 | 12.6 | 3000 | 0.4994 | 0.5341 | |
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| 0.8462 | 13.65 | 3250 | 0.4626 | 0.5262 | |
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| 0.8334 | 14.7 | 3500 | 0.4593 | 0.5197 | |
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| 0.842 | 15.75 | 3750 | 0.4651 | 0.5126 | |
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| 0.7678 | 16.81 | 4000 | 0.4687 | 0.5120 | |
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| 0.7873 | 17.86 | 4250 | 0.4716 | 0.5070 | |
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| 0.7486 | 18.91 | 4500 | 0.4657 | 0.5033 | |
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| 0.7073 | 19.96 | 4750 | 0.4658 | 0.5037 | |
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### Framework versions |
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- Transformers 4.17.0 |
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- Pytorch 1.11.0+cu102 |
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- Datasets 2.0.0 |
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- Tokenizers 0.11.6 |
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