HarrisDePerceptron
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update model card README.md
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README.md
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---
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language:
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- ur
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license: apache-2.0
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tags:
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- automatic-speech-recognition
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- mozilla-foundation/common_voice_8_0
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- generated_from_trainer
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- ur
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- robust-speech-event
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datasets:
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- common_voice
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model-index:
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#
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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
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It achieves the following results on the evaluation set:
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- Loss:
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- Wer: 0.
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## Model description
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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:
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- total_train_batch_size:
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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:
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- num_epochs: 50.0
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.
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- Tokenizers 0.11.0
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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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#
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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: 0.9604
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- Wer: 0.6542
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## Model description
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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: 50
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- num_epochs: 50.0
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- mixed_precision_training: Native AMP
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| Training Loss | Epoch | Step | Validation Loss | Wer |
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|:-------------:|:-----:|:----:|:---------------:|:------:|
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| 9.5036 | 1.96 | 100 | 4.0538 | 1.0 |
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| 3.3669 | 3.92 | 200 | 3.2041 | 1.0 |
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| 3.1499 | 5.88 | 300 | 3.1220 | 1.0 |
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| 3.0271 | 7.84 | 400 | 2.9935 | 0.9970 |
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| 2.9565 | 9.8 | 500 | 2.9357 | 0.9993 |
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| 2.9184 | 11.76 | 600 | 2.9165 | 0.9963 |
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| 2.8832 | 13.73 | 700 | 2.8762 | 0.9911 |
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| 2.8407 | 15.69 | 800 | 2.8102 | 0.9970 |
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| 2.7007 | 17.65 | 900 | 2.4364 | 0.9963 |
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| 2.4206 | 19.61 | 1000 | 1.9852 | 0.9421 |
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| 2.0699 | 21.57 | 1100 | 1.4849 | 0.8343 |
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| 1.8311 | 23.53 | 1200 | 1.3084 | 0.7801 |
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| 1.7127 | 25.49 | 1300 | 1.2040 | 0.7446 |
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| 1.6239 | 27.45 | 1400 | 1.1359 | 0.7280 |
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| 1.5654 | 29.41 | 1500 | 1.0688 | 0.7159 |
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| 1.4965 | 31.37 | 1600 | 1.0520 | 0.6985 |
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| 1.445 | 33.33 | 1700 | 1.0314 | 0.6878 |
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| 1.4095 | 35.29 | 1800 | 1.0063 | 0.6712 |
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| 1.3853 | 37.25 | 1900 | 0.9848 | 0.6701 |
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| 1.3558 | 39.22 | 2000 | 0.9738 | 0.6731 |
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| 1.3415 | 41.18 | 2100 | 0.9656 | 0.6646 |
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| 1.3102 | 43.14 | 2200 | 0.9632 | 0.6557 |
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| 1.309 | 45.1 | 2300 | 0.9496 | 0.6557 |
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| 1.2993 | 47.06 | 2400 | 0.9609 | 0.6550 |
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| 1.2695 | 49.02 | 2500 | 0.9604 | 0.6542 |
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### Framework versions
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- Transformers 4.17.0.dev0
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- Pytorch 1.10.2+cu102
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- Datasets 1.18.3
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- Tokenizers 0.11.0
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