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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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- tr
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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: hello_2b
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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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# hello_2b
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This model is a fine-tuned version of [facebook/wav2vec2-xls-r-2b](https://huggingface.co/facebook/wav2vec2-xls-r-2b) on the COMMON_VOICE - TR dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.2725
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- Wer: 0.9531
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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: 1e-05
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- train_batch_size: 2
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- eval_batch_size: 8
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- seed: 42
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- distributed_type: multi-GPU
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- num_devices: 2
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- gradient_accumulation_steps: 8
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- total_train_batch_size: 32
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- total_eval_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: 500
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- num_epochs: 30.0
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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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| 3.1646 | 0.92 | 100 | 3.2106 | 1.0 |
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| 0.368 | 1.85 | 200 | 2.9963 | 1.0 |
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| 0.2252 | 2.77 | 300 | 2.8078 | 0.9999 |
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| 0.1546 | 3.7 | 400 | 2.3458 | 0.9996 |
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| 0.1468 | 4.63 | 500 | 2.0086 | 0.9986 |
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| 0.1261 | 5.55 | 600 | 1.8269 | 0.9985 |
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| 0.1206 | 6.48 | 700 | 1.7347 | 0.9956 |
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| 0.1959 | 7.4 | 800 | 1.6819 | 0.9955 |
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| 0.0502 | 8.33 | 900 | 1.6809 | 0.9965 |
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| 0.0811 | 9.26 | 1000 | 1.6674 | 0.9916 |
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| 0.0534 | 10.18 | 1100 | 1.5719 | 0.9898 |
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| 0.0402 | 11.11 | 1200 | 1.4620 | 0.9821 |
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| 0.057 | 12.04 | 1300 | 1.3015 | 0.9554 |
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| 0.0385 | 12.96 | 1400 | 1.3798 | 0.9600 |
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| 0.0422 | 13.88 | 1500 | 1.3538 | 0.9699 |
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| 0.014 | 14.81 | 1600 | 1.2507 | 0.9443 |
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| 0.0232 | 15.74 | 1700 | 1.3318 | 0.9465 |
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| 0.0554 | 16.66 | 1800 | 1.2784 | 0.9462 |
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| 0.0316 | 17.59 | 1900 | 1.2503 | 0.9481 |
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| 0.0524 | 18.51 | 2000 | 1.3920 | 0.9604 |
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| 0.0142 | 19.44 | 2100 | 1.4224 | 0.9698 |
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| 0.0288 | 20.37 | 2200 | 1.3475 | 0.9635 |
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| 0.0106 | 21.29 | 2300 | 1.2232 | 0.9264 |
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| 0.0396 | 22.22 | 2400 | 1.3323 | 0.9615 |
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| 0.0349 | 23.15 | 2500 | 1.2741 | 0.9587 |
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| 0.0121 | 24.07 | 2600 | 1.2671 | 0.9586 |
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| 0.0224 | 24.99 | 2700 | 1.3001 | 0.9611 |
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| 0.0449 | 25.92 | 2800 | 1.2777 | 0.9572 |
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| 0.0186 | 26.85 | 2900 | 1.2766 | 0.9607 |
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| 0.0365 | 27.77 | 3000 | 1.2935 | 0.9598 |
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| 0.0105 | 28.7 | 3100 | 1.2761 | 0.9588 |
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| 0.021 | 29.63 | 3200 | 1.2686 | 0.9528 |
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### Framework versions
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- Transformers 4.13.0.dev0
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- Pytorch 1.10.0
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- Datasets 1.15.2.dev0
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- Tokenizers 0.10.3
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