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--- |
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base_model: microsoft/unispeech-sat-base |
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tags: |
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- generated_from_trainer |
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metrics: |
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- accuracy |
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- f1 |
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- recall |
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- precision |
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model-index: |
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- name: unispeech-sat-base-finetuned-common_voice |
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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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# unispeech-sat-base-finetuned-common_voice |
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This model is a fine-tuned version of [microsoft/unispeech-sat-base](https://huggingface.co./microsoft/unispeech-sat-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0013 |
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- Accuracy: 1.0 |
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- F1: 1.0 |
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- Recall: 1.0 |
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- Precision: 1.0 |
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- Mcc: 1.0 |
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- Auc: 1.0 |
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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: 3e-05 |
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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: 4 |
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- total_train_batch_size: 32 |
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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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- mixed_precision_training: Native AMP |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Recall | Precision | Mcc | Auc | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:------:|:---------:|:------:|:------:| |
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| 0.1326 | 1.0 | 50 | 0.0283 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 | |
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| 0.1323 | 2.0 | 100 | 0.0450 | 0.9925 | 0.9925 | 0.9925 | 0.9928 | 0.9907 | 0.9994 | |
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| 0.0499 | 3.0 | 150 | 0.0081 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 | |
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| 0.0183 | 4.0 | 200 | 0.0037 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.024 | 5.0 | 250 | 0.0026 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0326 | 6.0 | 300 | 0.0020 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0172 | 7.0 | 350 | 0.0017 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0053 | 8.0 | 400 | 0.0015 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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| 0.0034 | 9.0 | 450 | 0.0050 | 0.9975 | 0.9975 | 0.9975 | 0.9975 | 0.9969 | 1.0 | |
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| 0.014 | 10.0 | 500 | 0.0013 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | 1.0 | |
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### Framework versions |
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- Transformers 4.40.2 |
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- Pytorch 2.2.1+cu121 |
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- Datasets 2.19.1 |
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- Tokenizers 0.19.1 |
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