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library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-custom
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-custom
This model is a fine-tuned version of [facebook/hubert-base-ls960](https://huggingface.co/facebook/hubert-base-ls960) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6927
- Accuracy: 0.5156
## 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: 4
- eval_batch_size: 4
- seed: 42
- 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
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6835 | 2.7778 | 100 | 0.6809 | 0.5625 |
| 0.6998 | 5.5556 | 200 | 0.6928 | 0.5156 |
| 0.711 | 8.3333 | 300 | 0.7050 | 0.4844 |
| 0.6965 | 11.1111 | 400 | 0.6932 | 0.4844 |
| 0.6994 | 13.8889 | 500 | 0.7030 | 0.4844 |
| 0.7002 | 16.6667 | 600 | 0.6927 | 0.5156 |
| 0.6982 | 19.4444 | 700 | 0.6935 | 0.4844 |
| 0.6981 | 22.2222 | 800 | 0.6928 | 0.5156 |
| 0.6942 | 25.0 | 900 | 0.6923 | 0.5156 |
| 0.6951 | 27.7778 | 1000 | 0.6927 | 0.5156 |
### Framework versions
- Transformers 4.51.1
- Pytorch 2.6.0+cu124
- Datasets 3.5.0
- Tokenizers 0.21.1
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