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---
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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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- precision
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- recall
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- f1
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model-index:
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- name: hubert-classifier
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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-classifier
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This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
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It achieves the following results on the evaluation set:
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- Loss: 3.4231
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- Accuracy: 0.0993
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- Precision: 0.0191
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- Recall: 0.0993
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- F1: 0.0296
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- Binary: 0.3603
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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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- num_epochs: 10
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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 | Precision | Recall | F1 | Binary |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
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| No log | 0.86 | 50 | 4.4031 | 0.0218 | 0.0042 | 0.0218 | 0.0061 | 0.1886 |
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| No log | 1.72 | 100 | 4.1752 | 0.0363 | 0.0204 | 0.0363 | 0.0100 | 0.3102 |
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| No log | 2.59 | 150 | 3.9334 | 0.0363 | 0.0159 | 0.0363 | 0.0125 | 0.3102 |
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| No log | 3.45 | 200 | 3.7751 | 0.0557 | 0.0270 | 0.0557 | 0.0268 | 0.3266 |
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| No log | 4.31 | 250 | 3.6877 | 0.0775 | 0.0241 | 0.0775 | 0.0314 | 0.3383 |
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| No log | 5.17 | 300 | 3.5839 | 0.0920 | 0.0220 | 0.0920 | 0.0329 | 0.3550 |
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| No log | 6.03 | 350 | 3.5119 | 0.0920 | 0.0219 | 0.0920 | 0.0327 | 0.3586 |
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| No log | 6.9 | 400 | 3.4851 | 0.0872 | 0.0274 | 0.0872 | 0.0283 | 0.3508 |
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| No log | 7.76 | 450 | 3.4593 | 0.0920 | 0.0221 | 0.0920 | 0.0312 | 0.3552 |
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| 3.8751 | 8.62 | 500 | 3.4240 | 0.1017 | 0.0223 | 0.1017 | 0.0328 | 0.3610 |
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| 3.8751 | 9.48 | 550 | 3.4231 | 0.0993 | 0.0191 | 0.0993 | 0.0296 | 0.3603 |
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### Framework versions
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- Transformers 4.38.2
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- Pytorch 2.3.0
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- Datasets 2.19.1
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- Tokenizers 0.15.1
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