---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-eos_poc5_ge-di-v5
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# hubert-base-ls960-finetuned-eos_poc5_ge-di-v5

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: 0.8936
- Accuracy: 0.6772

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Use 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.0044        | 1.0   | 302  | 1.0290          | 0.5622   |
| 0.7936        | 2.0   | 604  | 1.0197          | 0.5640   |
| 0.9923        | 3.0   | 906  | 0.9170          | 0.6122   |
| 0.9078        | 4.0   | 1208 | 0.9016          | 0.6160   |
| 0.8268        | 5.0   | 1510 | 0.9285          | 0.6345   |
| 0.7044        | 6.0   | 1812 | 0.8985          | 0.6494   |
| 0.6689        | 7.0   | 2114 | 0.9121          | 0.6549   |
| 0.7087        | 8.0   | 2416 | 0.8722          | 0.6735   |
| 0.6809        | 9.0   | 2718 | 0.8894          | 0.6735   |
| 0.7639        | 10.0  | 3020 | 0.8936          | 0.6772   |


### Framework versions

- Transformers 4.47.1
- Pytorch 2.5.1+cu121
- Datasets 3.2.0
- Tokenizers 0.21.0