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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: 3.2824
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- Accuracy: 0.1864
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- Precision: 0.1087
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- Recall: 0.1864
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- F1: 0.1114
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- Binary: 0.4189
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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 | 4.2455 | 0.0533 | 0.0410 | 0.0533 | 0.0255 | 0.3252 |
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| No log | 1.72 | 100 | 3.9851 | 0.0630 | 0.0179 | 0.0630 | 0.0163 | 0.3249 |
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| No log | 2.59 | 150 | 3.7681 | 0.0726 | 0.0401 | 0.0726 | 0.0283 | 0.3421 |
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| No log | 3.45 | 200 | 3.7448 | 0.0678 | 0.0383 | 0.0678 | 0.0252 | 0.3167 |
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| No log | 4.31 | 250 | 3.5775 | 0.0896 | 0.0447 | 0.0896 | 0.0413 | 0.3453 |
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| No log | 5.17 | 300 | 3.5078 | 0.0969 | 0.0380 | 0.0969 | 0.0400 | 0.3482 |
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| No log | 6.03 | 350 | 3.4008 | 0.1283 | 0.0445 | 0.1283 | 0.0587 | 0.3777 |
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| No log | 6.9 | 400 | 3.3443 | 0.1550 | 0.1089 | 0.1550 | 0.0850 | 0.3983 |
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| No log | 7.76 | 450 | 3.2965 | 0.1792 | 0.1052 | 0.1792 | 0.1056 | 0.4177 |
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| 3.768 | 8.62 | 500 | 3.2824 | 0.1864 | 0.1087 | 0.1864 | 0.1114 | 0.4189 |
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| 3.768 | 9.48 | 550 | 3.2609 | 0.2058 | 0.1339 | 0.2058 | 0.1251 | 0.4332 |
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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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