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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: 0.6810 |
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- Accuracy: 0.6471 |
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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: 5e-05 |
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- train_batch_size: 16 |
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- eval_batch_size: 16 |
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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: cosine |
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- lr_scheduler_warmup_ratio: 0.1 |
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- lr_scheduler_warmup_steps: 500 |
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- num_epochs: 25 |
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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 | 5 | 0.6810 | 0.6471 | |
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| 0.6835 | 2.0 | 10 | 0.6785 | 0.6471 | |
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| 0.6835 | 3.0 | 15 | 0.6748 | 0.6471 | |
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| 0.6745 | 4.0 | 20 | 0.6715 | 0.6471 | |
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| 0.6745 | 5.0 | 25 | 0.6688 | 0.6471 | |
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| 0.6773 | 6.0 | 30 | 0.6622 | 0.6471 | |
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| 0.6773 | 7.0 | 35 | 0.6585 | 0.6471 | |
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| 0.6663 | 8.0 | 40 | 0.6553 | 0.6471 | |
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| 0.6663 | 9.0 | 45 | 0.6539 | 0.6471 | |
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| 0.6254 | 10.0 | 50 | 0.6514 | 0.6471 | |
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| 0.6254 | 11.0 | 55 | 0.6506 | 0.6471 | |
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| 0.6697 | 12.0 | 60 | 0.6498 | 0.6471 | |
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| 0.6697 | 13.0 | 65 | 0.6604 | 0.6471 | |
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| 0.6485 | 14.0 | 70 | 0.6556 | 0.6471 | |
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| 0.6485 | 15.0 | 75 | 0.6504 | 0.6471 | |
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| 0.6802 | 16.0 | 80 | 0.6636 | 0.6471 | |
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| 0.6802 | 17.0 | 85 | 0.6521 | 0.6471 | |
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| 0.6737 | 18.0 | 90 | 0.6494 | 0.6471 | |
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| 0.6737 | 19.0 | 95 | 0.6494 | 0.6471 | |
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| 0.6687 | 20.0 | 100 | 0.6493 | 0.6471 | |
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| 0.6687 | 21.0 | 105 | 0.6500 | 0.6471 | |
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| 0.6456 | 22.0 | 110 | 0.6500 | 0.6471 | |
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| 0.6456 | 23.0 | 115 | 0.6493 | 0.6471 | |
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| 0.6448 | 24.0 | 120 | 0.6493 | 0.6471 | |
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| 0.6448 | 25.0 | 125 | 0.6495 | 0.6471 | |
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### Framework versions |
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- Transformers 4.26.1 |
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- Pytorch 1.13.1+cu116 |
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- Datasets 2.9.0 |
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- Tokenizers 0.13.2 |
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