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--- |
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license: apache-2.0 |
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base_model: facebook/wav2vec2-base |
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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: test-model |
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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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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/khackho01125-CMC-University/huggingface/runs/fddm7hnz) |
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# test-model |
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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: 0.2342 |
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- Accuracy: 0.9356 |
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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: 8 |
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- seed: 42 |
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- gradient_accumulation_steps: 4 |
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- total_train_batch_size: 64 |
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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: 0.3 |
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- training_steps: 600 |
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- mixed_precision_training: Native AMP |
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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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| 1.0226 | 0.9639 | 60 | 0.8861 | 0.5453 | |
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| 0.8233 | 1.9277 | 120 | 0.6863 | 0.7123 | |
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| 0.672 | 2.8916 | 180 | 0.4994 | 0.7988 | |
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| 0.5346 | 3.8554 | 240 | 0.4163 | 0.8692 | |
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| 0.4306 | 4.8193 | 300 | 0.3459 | 0.8934 | |
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| 0.3544 | 5.7831 | 360 | 0.3317 | 0.8853 | |
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| 0.3214 | 6.7470 | 420 | 0.2763 | 0.9115 | |
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| 0.2778 | 7.7108 | 480 | 0.2877 | 0.9296 | |
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| 0.2264 | 8.6747 | 540 | 0.2487 | 0.9336 | |
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| 0.2127 | 9.6386 | 600 | 0.2342 | 0.9356 | |
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### Framework versions |
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- Transformers 4.42.3 |
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- Pytorch 2.1.2 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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