Thamer Smadi
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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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- speech_commands
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metrics:
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- accuracy
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model-index:
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- name: wav2vec-fine_tuned-speech_command2
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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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# wav2vec-fine_tuned-speech_command2
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the speech_commands dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.1040
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- Accuracy: 0.9735
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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: 0.0003
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- train_batch_size: 256
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- eval_batch_size: 256
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- seed: 42
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- gradient_accumulation_steps: 4
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- total_train_batch_size: 1024
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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_ratio: 0.1
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- num_epochs: 10
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 1.3874 | 1.0 | 50 | 0.9633 | 0.9229 |
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| 0.5144 | 2.0 | 100 | 0.4398 | 0.9138 |
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| 0.3538 | 3.0 | 150 | 0.1688 | 0.9651 |
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| 0.2956 | 4.0 | 200 | 0.1622 | 0.9623 |
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| 0.2662 | 5.0 | 250 | 0.1425 | 0.9665 |
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| 0.2122 | 6.0 | 300 | 0.1301 | 0.9682 |
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| 0.1948 | 7.0 | 350 | 0.1232 | 0.9693 |
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| 0.1837 | 8.0 | 400 | 0.1116 | 0.9734 |
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| 0.1631 | 9.0 | 450 | 0.1041 | 0.9734 |
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| 0.1441 | 10.0 | 500 | 0.1040 | 0.9735 |
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### Framework versions
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- Transformers 4.30.2
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- Pytorch 2.0.0
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- Datasets 2.1.0
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- Tokenizers 0.13.3
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