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update model card README.md
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README.md
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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-base-checkpoint-6
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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-base-checkpoint-6
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This model is a fine-tuned version of [jiobiala24/wav2vec2-base-checkpoint-5](https://huggingface.co/jiobiala24/wav2vec2-base-checkpoint-5) on the common_voice dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.9738
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- Wer: 0.3323
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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: 32
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- eval_batch_size: 8
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- seed: 42
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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: 30
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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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| 0.3435 | 1.82 | 1000 | 0.5637 | 0.3419 |
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| 0.2599 | 3.65 | 2000 | 0.5804 | 0.3473 |
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| 0.2043 | 5.47 | 3000 | 0.6481 | 0.3474 |
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| 0.1651 | 7.3 | 4000 | 0.6937 | 0.3452 |
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| 0.1376 | 9.12 | 5000 | 0.7221 | 0.3429 |
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| 0.118 | 10.95 | 6000 | 0.7634 | 0.3441 |
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| 0.105 | 12.77 | 7000 | 0.7789 | 0.3444 |
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| 0.0925 | 14.6 | 8000 | 0.8209 | 0.3444 |
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| 0.0863 | 16.42 | 9000 | 0.8293 | 0.3440 |
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| 0.0756 | 18.25 | 10000 | 0.8553 | 0.3412 |
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| 0.0718 | 20.07 | 11000 | 0.9006 | 0.3430 |
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| 0.0654 | 21.9 | 12000 | 0.9541 | 0.3458 |
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| 0.0605 | 23.72 | 13000 | 0.9400 | 0.3350 |
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| 0.0552 | 25.55 | 14000 | 0.9547 | 0.3363 |
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| 0.0543 | 27.37 | 15000 | 0.9715 | 0.3348 |
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| 0.0493 | 29.2 | 16000 | 0.9738 | 0.3323 |
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### Framework versions
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- Transformers 4.11.3
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- Pytorch 1.10.0+cu111
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- Datasets 1.13.3
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- Tokenizers 0.10.3
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