---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-ie
  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-finetuned-ie

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:
- Accuracy: 0.6130
- Loss: 1.1686

## 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
- gradient_accumulation_steps: 4
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Accuracy | Validation Loss |
|:-------------:|:-----:|:----:|:--------:|:---------------:|
| 1.3145        | 1.0   | 51   | 0.3647   | 1.2880          |
| 1.137         | 2.0   | 102  | 0.4316   | 1.1491          |
| 1.0227        | 3.0   | 153  | 0.5829   | 0.9724          |
| 0.9822        | 4.0   | 204  | 0.5645   | 0.9873          |
| 0.9084        | 5.0   | 255  | 0.5742   | 1.0029          |
| 0.8217        | 6.0   | 306  | 0.5887   | 1.0273          |
| 0.779         | 7.0   | 357  | 0.6120   | 0.9774          |
| 0.7444        | 8.0   | 408  | 0.6208   | 1.0336          |
| 0.6894        | 9.0   | 459  | 0.6140   | 0.9925          |
| 0.6486        | 10.0  | 510  | 0.6043   | 1.0733          |
| 0.6669        | 11.0  | 561  | 0.6305   | 1.0746          |
| 0.6184        | 12.0  | 612  | 0.6072   | 1.1670          |
| 0.5231        | 13.0  | 663  | 0.6052   | 1.1792          |
| 0.5381        | 14.0  | 714  | 0.6198   | 1.1432          |
| 0.5251        | 15.0  | 765  | 0.6130   | 1.1686          |


### Framework versions

- Transformers 4.26.1
- Pytorch 1.13.0
- Datasets 2.10.1
- Tokenizers 0.13.2