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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-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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- precision |
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- recall |
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model-index: |
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- name: results |
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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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# results |
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This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the None dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.9132 |
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- Accuracy: 0.6351 |
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- F1: 0.6301 |
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- Precision: 0.6315 |
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- Recall: 0.6351 |
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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: 2e-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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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
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- lr_scheduler_type: linear |
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- num_epochs: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall | |
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|:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:| |
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| 0.586 | 1.0 | 855 | 0.6272 | 0.6316 | 0.5289 | 0.5719 | 0.6316 | |
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| 0.6905 | 2.0 | 1710 | 0.5821 | 0.6520 | 0.5420 | 0.4804 | 0.6520 | |
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| 0.5642 | 3.0 | 2565 | 0.6012 | 0.6497 | 0.5396 | 0.4769 | 0.6497 | |
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| 0.6263 | 4.0 | 3420 | 0.6040 | 0.6526 | 0.5903 | 0.6403 | 0.6526 | |
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| 0.7556 | 5.0 | 4275 | 0.6088 | 0.6485 | 0.5406 | 0.4838 | 0.6485 | |
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| 0.4614 | 6.0 | 5130 | 0.6061 | 0.6614 | 0.6348 | 0.6523 | 0.6614 | |
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| 0.4232 | 7.0 | 5985 | 0.6184 | 0.6456 | 0.6401 | 0.6355 | 0.6456 | |
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| 0.519 | 8.0 | 6840 | 0.6186 | 0.6538 | 0.5449 | 0.4874 | 0.6538 | |
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| 0.4847 | 9.0 | 7695 | 0.6226 | 0.6421 | 0.5652 | 0.5948 | 0.6421 | |
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| 0.5505 | 10.0 | 8550 | 0.6857 | 0.6363 | 0.5903 | 0.6241 | 0.6363 | |
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| 0.5499 | 11.0 | 9405 | 0.6684 | 0.6491 | 0.6462 | 0.6470 | 0.6491 | |
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| 0.2869 | 12.0 | 10260 | 0.7500 | 0.6468 | 0.6341 | 0.6389 | 0.6468 | |
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| 0.2607 | 13.0 | 11115 | 0.9291 | 0.6351 | 0.6354 | 0.6357 | 0.6351 | |
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| 0.3495 | 14.0 | 11970 | 1.1298 | 0.6444 | 0.6415 | 0.6396 | 0.6444 | |
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| 0.2483 | 15.0 | 12825 | 1.3714 | 0.6246 | 0.6181 | 0.6320 | 0.6246 | |
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| 0.3764 | 16.0 | 13680 | 1.4325 | 0.6515 | 0.6454 | 0.6475 | 0.6515 | |
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| 0.373 | 17.0 | 14535 | 1.6233 | 0.6491 | 0.6473 | 0.6457 | 0.6491 | |
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| 0.0677 | 18.0 | 15390 | 1.7408 | 0.6450 | 0.6434 | 0.6429 | 0.6450 | |
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| 0.0665 | 19.0 | 16245 | 1.8868 | 0.6351 | 0.6296 | 0.6316 | 0.6351 | |
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| 0.0044 | 20.0 | 17100 | 1.9132 | 0.6351 | 0.6301 | 0.6315 | 0.6351 | |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.1+cu121 |
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- Datasets 2.19.2 |
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- Tokenizers 0.19.1 |
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