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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: 3.2561
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- Accuracy: 0.2155
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- Precision: 0.1870
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- Recall: 0.2155
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- F1: 0.1453
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- Binary: 0.4380
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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 | 4.2865 | 0.0291 | 0.0034 | 0.0291 | 0.0043 | 0.2661 |
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| No log | 1.72 | 100 | 4.0141 | 0.0460 | 0.0306 | 0.0460 | 0.0187 | 0.3199 |
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| No log | 2.59 | 150 | 3.8172 | 0.0630 | 0.0204 | 0.0630 | 0.0214 | 0.3378 |
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| No log | 3.45 | 200 | 3.7045 | 0.0896 | 0.0534 | 0.0896 | 0.0533 | 0.3431 |
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| No log | 4.31 | 250 | 3.5695 | 0.1308 | 0.0844 | 0.1308 | 0.0796 | 0.3785 |
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| No log | 5.17 | 300 | 3.4883 | 0.1622 | 0.1140 | 0.1622 | 0.1002 | 0.3954 |
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| No log | 6.03 | 350 | 3.4447 | 0.1622 | 0.1145 | 0.1622 | 0.1005 | 0.3925 |
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| No log | 6.9 | 400 | 3.3482 | 0.1671 | 0.0972 | 0.1671 | 0.1026 | 0.4077 |
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| No log | 7.76 | 450 | 3.3042 | 0.1961 | 0.1424 | 0.1961 | 0.1295 | 0.4228 |
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| 3.7796 | 8.62 | 500 | 3.2724 | 0.2131 | 0.1898 | 0.2131 | 0.1472 | 0.4370 |
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| 3.7796 | 9.48 | 550 | 3.2561 | 0.2155 | 0.1870 | 0.2155 | 0.1453 | 0.4380 |
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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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