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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-no-softmax-quality-daps |
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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-no-softmax-quality-daps |
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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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- Loss: 0.0422 |
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- Accuracy: 0.9925 |
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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: 128 |
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- eval_batch_size: 128 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 512 |
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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: 15 |
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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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| 0.6897 | 0.9630 | 13 | 0.6386 | 0.9318 | |
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| 0.6402 | 2.0 | 27 | 0.3482 | 0.9943 | |
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| 0.2867 | 2.9630 | 40 | 0.1576 | 0.9938 | |
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| 0.1729 | 4.0 | 54 | 0.0806 | 0.9960 | |
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| 0.1058 | 4.9630 | 67 | 0.0539 | 0.9952 | |
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| 0.0542 | 6.0 | 81 | 0.0446 | 0.9947 | |
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| 0.0393 | 6.9630 | 94 | 0.0409 | 0.9943 | |
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| 0.0398 | 8.0 | 108 | 0.0401 | 0.9938 | |
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| 0.0325 | 8.9630 | 121 | 0.0459 | 0.9921 | |
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| 0.0251 | 10.0 | 135 | 0.0444 | 0.9925 | |
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| 0.0331 | 10.9630 | 148 | 0.0418 | 0.9930 | |
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| 0.0185 | 12.0 | 162 | 0.0373 | 0.9930 | |
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| 0.0254 | 12.9630 | 175 | 0.0367 | 0.9930 | |
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| 0.0238 | 14.0 | 189 | 0.0423 | 0.9925 | |
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| 0.023 | 14.4444 | 195 | 0.0422 | 0.9925 | |
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### Framework versions |
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- Transformers 4.40.1 |
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- Pytorch 2.3.0 |
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- Datasets 2.12.0 |
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- Tokenizers 0.19.1 |
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