transformers tensorboard safetensors hubert audio-classification generated_from_trainer base_model:facebook/hubert-base-ls960 license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-ks-3s
  results: []
---

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# hubert-base-ls960-finetuned-ks-3s

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: 0.0812
- Accuracy: 0.9937

## 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
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.6706        | 1.0   | 50   | 0.4022          | 0.9894   |
| 0.2319        | 2.0   | 100  | 0.1405          | 0.9919   |
| 0.1771        | 3.0   | 150  | 0.1081          | 0.9875   |
| 0.1656        | 4.0   | 200  | 0.0812          | 0.9937   |


### Framework versions

- Transformers 4.36.2
- Pytorch 2.1.2+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
