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README.md
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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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<!-- 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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# HuBERT-base-F4-New
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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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## 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: 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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### Training results
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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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### Framework versions
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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
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