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

# ckpts

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: 0.2980
- Accuracy: 0.9545

## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.1628        | 1.0   | 223  | 0.7126          | 0.7727   |
| 0.6562        | 2.0   | 446  | 0.5069          | 0.8485   |
| 0.4199        | 3.0   | 669  | 0.3570          | 0.8990   |
| 0.325         | 4.0   | 892  | 0.2092          | 0.9394   |
| 0.2217        | 5.0   | 1115 | 0.2392          | 0.9444   |
| 0.1831        | 6.0   | 1338 | 0.2754          | 0.9293   |
| 0.1598        | 7.0   | 1561 | 0.3294          | 0.9343   |
| 0.1676        | 8.0   | 1784 | 0.2669          | 0.9495   |
| 0.1597        | 9.0   | 2007 | 0.3438          | 0.9293   |
| 0.1132        | 10.0  | 2230 | 0.3159          | 0.9444   |
| 0.1224        | 11.0  | 2453 | 0.2980          | 0.9545   |
| 0.095         | 12.0  | 2676 | 0.2970          | 0.9444   |
| 0.1087        | 13.0  | 2899 | 0.3449          | 0.9343   |
| 0.1254        | 14.0  | 3122 | 0.3198          | 0.9444   |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2