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README.md ADDED
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+ ---
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+ license: apache-2.0
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+ base_model: jonatasgrosman/wav2vec2-large-xlsr-53-english
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+ tags:
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+ - generated_from_trainer
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+ datasets:
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+ - minds14
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+ metrics:
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+ - wer
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+ model-index:
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+ - name: English_asr_model
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+ results:
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+ - task:
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+ name: Automatic Speech Recognition
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+ type: automatic-speech-recognition
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+ dataset:
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+ name: minds14
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+ type: minds14
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+ config: en-US
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+ split: None
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+ args: en-US
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+ metrics:
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+ - name: Wer
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+ type: wer
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+ value: 0.7368421052631579
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+ ---
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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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+
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+ # English_asr_model
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+
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+ This model is a fine-tuned version of [jonatasgrosman/wav2vec2-large-xlsr-53-english](https://huggingface.co/jonatasgrosman/wav2vec2-large-xlsr-53-english) on the minds14 dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 3.8502
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+ - Wer: 0.7368
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 250
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+ - training_steps: 1000
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+ - mixed_precision_training: Native AMP
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Wer |
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+ |:-------------:|:------:|:----:|:---------------:|:------:|
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+ | 0.0033 | 500.0 | 500 | 4.0590 | 0.7193 |
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+ | 0.0012 | 1000.0 | 1000 | 3.8502 | 0.7368 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.40.0
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+ - Pytorch 2.2.1+cu121
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+ - Datasets 2.19.0
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+ - Tokenizers 0.19.1
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