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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: hubert-classifier
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# hubert-classifier
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2824
- Accuracy: 0.1864
- Precision: 0.1087
- Recall: 0.1864
- F1: 0.1114
- Binary: 0.4189
## Model description
More information needed
## Intended uses & limitations
More information needed
## Training and evaluation data
More information needed
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 3e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| No log | 0.86 | 50 | 4.2455 | 0.0533 | 0.0410 | 0.0533 | 0.0255 | 0.3252 |
| No log | 1.72 | 100 | 3.9851 | 0.0630 | 0.0179 | 0.0630 | 0.0163 | 0.3249 |
| No log | 2.59 | 150 | 3.7681 | 0.0726 | 0.0401 | 0.0726 | 0.0283 | 0.3421 |
| No log | 3.45 | 200 | 3.7448 | 0.0678 | 0.0383 | 0.0678 | 0.0252 | 0.3167 |
| No log | 4.31 | 250 | 3.5775 | 0.0896 | 0.0447 | 0.0896 | 0.0413 | 0.3453 |
| No log | 5.17 | 300 | 3.5078 | 0.0969 | 0.0380 | 0.0969 | 0.0400 | 0.3482 |
| No log | 6.03 | 350 | 3.4008 | 0.1283 | 0.0445 | 0.1283 | 0.0587 | 0.3777 |
| No log | 6.9 | 400 | 3.3443 | 0.1550 | 0.1089 | 0.1550 | 0.0850 | 0.3983 |
| No log | 7.76 | 450 | 3.2965 | 0.1792 | 0.1052 | 0.1792 | 0.1056 | 0.4177 |
| 3.768 | 8.62 | 500 | 3.2824 | 0.1864 | 0.1087 | 0.1864 | 0.1114 | 0.4189 |
| 3.768 | 9.48 | 550 | 3.2609 | 0.2058 | 0.1339 | 0.2058 | 0.1251 | 0.4332 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1
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