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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-fsc
  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-fsc

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: 0.0230
- Accuracy: 0.9939

## 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: 0.0005
- train_batch_size: 48
- eval_batch_size: 48
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 192
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 25

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Accuracy |
|:-------------:|:------:|:----:|:---------------:|:--------:|
| No log        | 0.9959 | 120  | 0.0706          | 0.9873   |
| No log        | 2.0    | 241  | 0.0607          | 0.9868   |
| No log        | 2.9959 | 361  | 0.0661          | 0.9831   |
| No log        | 4.0    | 482  | 0.0518          | 0.9839   |
| No log        | 4.9959 | 602  | 0.0230          | 0.9939   |
| No log        | 6.0    | 723  | 0.0516          | 0.9858   |
| No log        | 6.9959 | 843  | 0.0292          | 0.9937   |
| No log        | 8.0    | 964  | 0.0276          | 0.9929   |
| 0.2849        | 8.9959 | 1084 | 0.0301          | 0.9937   |
| 0.2849        | 10.0   | 1205 | 0.0279          | 0.9937   |


### Framework versions

- Transformers 4.43.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1