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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base-960h |
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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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model-index: |
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- name: wav2vec2-base-960h |
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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-960h |
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This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co./facebook/wav2vec2-base-960h) on an unknown dataset. |
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It achieves the following results on the evaluation set: |
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- Accuracy: 0.8830 |
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- Loss: 0.4259 |
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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: 5 |
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- eval_batch_size: 5 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 20 |
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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: 20 |
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### Training results |
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| Training Loss | Epoch | Step | Accuracy | Validation Loss | |
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|:-------------:|:-----:|:----:|:--------:|:---------------:| |
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| 0.7016 | 1.0 | 125 | 0.7933 | 0.6439 | |
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| 0.7121 | 2.0 | 250 | 0.5962 | 0.7870 | |
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| 0.4491 | 3.0 | 375 | 0.8782 | 0.4561 | |
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| 0.4606 | 4.0 | 500 | 0.8526 | 0.5664 | |
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| 0.425 | 5.0 | 625 | 0.8718 | 0.4652 | |
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| 0.4852 | 6.0 | 750 | 0.8397 | 0.5111 | |
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| 0.3023 | 7.0 | 875 | 0.8766 | 0.4319 | |
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| 0.2247 | 8.0 | 1000 | 0.8654 | 0.5093 | |
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| 0.4269 | 9.0 | 1125 | 0.8926 | 0.4148 | |
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| 0.348 | 10.0 | 1250 | 0.8846 | 0.3861 | |
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| 0.5049 | 11.0 | 1375 | 0.8814 | 0.4141 | |
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| 0.2305 | 12.0 | 1500 | 0.8878 | 0.3804 | |
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| 0.2839 | 13.0 | 1625 | 0.8990 | 0.3682 | |
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| 0.1739 | 14.0 | 1750 | 0.9022 | 0.3917 | |
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| 0.2808 | 15.0 | 1875 | 0.8926 | 0.4303 | |
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| 0.2306 | 16.0 | 2000 | 0.9006 | 0.3951 | |
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| 0.2766 | 17.0 | 2125 | 0.8974 | 0.4003 | |
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| 0.1212 | 18.0 | 2250 | 0.8910 | 0.3999 | |
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| 0.2822 | 19.0 | 2375 | 0.8766 | 0.4390 | |
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| 0.1391 | 20.0 | 2500 | 0.8830 | 0.4259 | |
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### Framework versions |
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- Transformers 4.40.1 |
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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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