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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: 0.2562 |
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- Accuracy: 0.9869 |
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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: 16 |
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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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| 2.4691 | 0.99 | 26 | 2.3935 | 0.2310 | |
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| 2.1621 | 1.99 | 52 | 2.0155 | 0.3202 | |
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| 1.8731 | 2.99 | 78 | 1.6397 | 0.7929 | |
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| 1.4521 | 3.99 | 104 | 1.2337 | 0.8940 | |
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| 1.101 | 4.99 | 130 | 0.9519 | 0.9393 | |
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| 0.9401 | 5.99 | 156 | 0.7686 | 0.975 | |
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| 0.7463 | 6.99 | 182 | 0.6338 | 0.9774 | |
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| 0.6555 | 7.99 | 208 | 0.5214 | 0.9810 | |
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| 0.5095 | 8.99 | 234 | 0.4228 | 0.9869 | |
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| 0.4152 | 9.99 | 260 | 0.3658 | 0.9857 | |
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| 0.3764 | 10.99 | 286 | 0.3311 | 0.9857 | |
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| 0.3325 | 11.99 | 312 | 0.2954 | 0.9881 | |
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| 0.3121 | 12.99 | 338 | 0.2797 | 0.9869 | |
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| 0.281 | 13.99 | 364 | 0.2650 | 0.9857 | |
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| 0.2627 | 14.99 | 390 | 0.2571 | 0.9869 | |
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| 0.2655 | 15.99 | 416 | 0.2562 | 0.9869 | |
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### Framework versions |
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- Transformers 4.21.1 |
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- Pytorch 1.12.1+cu113 |
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- Datasets 1.14.0 |
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- Tokenizers 0.12.1 |
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