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---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
- recall
model-index:
- name: hubert-base-ls960-2clsfinetuned-bmd-V1-20250201_145011-LOSO-section-out5
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-base-ls960-2clsfinetuned-bmd-V1-20250201_145011-LOSO-section-out5
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: 0.7381
- Accuracy: 0.7273
- F1: 0.7273
- Precision: 0.7273
- Recall: 0.7273
## 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: 0.0001
- train_batch_size: 4
- eval_batch_size: 4
- seed: 1968
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
| No log | 1.0 | 5 | 0.6674 | 0.5909 | 0.5087 | 0.775 | 0.5909 |
| 0.6794 | 2.0 | 10 | 0.6130 | 0.7727 | 0.7723 | 0.775 | 0.7727 |
| 0.6794 | 3.0 | 15 | 0.6236 | 0.6818 | 0.6645 | 0.7292 | 0.6818 |
| 0.5818 | 4.0 | 20 | 0.6672 | 0.6364 | 0.5810 | 0.7895 | 0.6364 |
| 0.5818 | 5.0 | 25 | 0.5214 | 0.7727 | 0.7723 | 0.775 | 0.7727 |
| 0.49 | 6.0 | 30 | 0.5402 | 0.7273 | 0.7273 | 0.7273 | 0.7273 |
| 0.49 | 7.0 | 35 | 0.7001 | 0.5455 | 0.5089 | 0.5647 | 0.5455 |
| 0.3862 | 8.0 | 40 | 0.5804 | 0.8182 | 0.8167 | 0.8291 | 0.8182 |
| 0.3862 | 9.0 | 45 | 0.6310 | 0.8182 | 0.8167 | 0.8291 | 0.8182 |
| 0.2812 | 10.0 | 50 | 0.7381 | 0.7273 | 0.7273 | 0.7273 | 0.7273 |
### Framework versions
- Transformers 4.48.2
- Pytorch 2.5.1+cu124
- Datasets 3.2.0
- Tokenizers 0.21.0
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