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End of training

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+ ---
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+ library_name: transformers
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+ license: apache-2.0
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+ base_model: facebook/hubert-base-ls960
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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: HuBERT-base-F4-New
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+ results: []
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+ ---
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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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+
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+ # HuBERT-base-F4-New
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+
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+ This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
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+ It achieves the following results on the evaluation set:
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+ - Loss: 0.9168
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+ - Accuracy: 0.8243
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+
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+ ## Model description
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+
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+ More information needed
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+
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+ ## Intended uses & limitations
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+
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+ More information needed
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+
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+ ## Training and evaluation data
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+
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+ More information needed
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+
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+ ## Training procedure
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+
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+ ### Training hyperparameters
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+
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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: 4
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+ - eval_batch_size: 4
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+ - seed: 42
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+ - gradient_accumulation_steps: 2
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+ - total_train_batch_size: 8
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+ - optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
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+ - lr_scheduler_type: linear
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+ - num_epochs: 9
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+
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+ ### Training results
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+
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+ | Training Loss | Epoch | Step | Validation Loss | Accuracy |
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+ |:-------------:|:------:|:----:|:---------------:|:--------:|
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+ | 1.1111 | 0.5714 | 400 | 0.9669 | 0.6179 |
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+ | 0.3809 | 1.1429 | 800 | 0.8532 | 0.6907 |
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+ | 0.675 | 1.7143 | 1200 | 0.7515 | 0.7286 |
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+ | 0.9991 | 2.2857 | 1600 | 0.8572 | 0.7136 |
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+ | 0.4101 | 2.8571 | 2000 | 0.6870 | 0.7800 |
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+ | 0.2602 | 3.4286 | 2400 | 0.7185 | 0.7893 |
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+ | 0.0872 | 4.0 | 2800 | 0.7470 | 0.7821 |
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+ | 0.3991 | 4.5714 | 3200 | 0.6624 | 0.8107 |
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+ | 0.1878 | 5.1429 | 3600 | 0.7700 | 0.8093 |
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+ | 0.7543 | 5.7143 | 4000 | 0.8749 | 0.7950 |
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+ | 0.5348 | 6.2857 | 4400 | 0.8467 | 0.8143 |
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+ | 0.055 | 6.8571 | 4800 | 0.8527 | 0.8229 |
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+ | 0.6014 | 7.4286 | 5200 | 0.9119 | 0.8150 |
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+ | 0.4068 | 8.0 | 5600 | 0.8984 | 0.8250 |
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+ | 0.0286 | 8.5714 | 6000 | 0.9168 | 0.8243 |
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+
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+
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+ ### Framework versions
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+
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+ - Transformers 4.57.1
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+ - Pytorch 2.8.0+cu126
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+ - Datasets 4.0.0
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+ - Tokenizers 0.22.1