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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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metrics: |
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- accuracy |
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model-index: |
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- name: wav2vec2-base-finetuned-ks |
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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-finetuned-ks |
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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: 0.7101 |
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- Accuracy: 0.7538 |
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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: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 128 |
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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 | Validation Loss | Accuracy | |
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|:-------------:|:-----:|:----:|:---------------:|:--------:| |
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| No log | 1.0 | 7 | 1.1448 | 0.5769 | |
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| 1.0433 | 2.0 | 14 | 1.0463 | 0.6077 | |
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| 0.9904 | 3.0 | 21 | 1.0912 | 0.5923 | |
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| 0.9904 | 4.0 | 28 | 1.0639 | 0.5769 | |
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| 0.8697 | 5.0 | 35 | 1.0283 | 0.6 | |
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| 0.7873 | 6.0 | 42 | 0.8870 | 0.7077 | |
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| 0.7873 | 7.0 | 49 | 0.8815 | 0.6538 | |
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| 0.7124 | 8.0 | 56 | 0.8828 | 0.6538 | |
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| 0.666 | 9.0 | 63 | 0.8701 | 0.6846 | |
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| 0.6376 | 10.0 | 70 | 0.8704 | 0.6692 | |
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| 0.6376 | 11.0 | 77 | 0.8934 | 0.7077 | |
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| 0.6552 | 12.0 | 84 | 0.8678 | 0.6692 | |
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| 0.5827 | 13.0 | 91 | 0.8471 | 0.7 | |
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| 0.5827 | 14.0 | 98 | 0.7986 | 0.7154 | |
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| 0.5557 | 15.0 | 105 | 0.7614 | 0.7462 | |
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| 0.5255 | 16.0 | 112 | 0.7847 | 0.7231 | |
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| 0.5255 | 17.0 | 119 | 0.7917 | 0.7154 | |
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| 0.5129 | 18.0 | 126 | 0.7101 | 0.7538 | |
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| 0.4621 | 19.0 | 133 | 0.7437 | 0.7385 | |
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| 0.4552 | 20.0 | 140 | 0.7404 | 0.7308 | |
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### Framework versions |
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- Transformers 4.11.3 |
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- Pytorch 1.10.0+cu111 |
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- Datasets 2.0.0 |
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- Tokenizers 0.10.3 |
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