---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: hubert-base-ls960-finetuned-ic-slurp-no-pretrain
  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-ic-slurp-no-pretrain

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: 3.2153
- Accuracy: 0.2587

## 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: 5e-05
- train_batch_size: 24
- eval_batch_size: 24
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 96
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 50

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.9001        | 1.0   | 527   | 3.9015          | 0.0736   |
| 3.8219        | 2.0   | 1055  | 3.8454          | 0.0766   |
| 3.7453        | 3.0   | 1582  | 3.7615          | 0.0837   |
| 3.7202        | 4.0   | 2110  | 3.7143          | 0.0912   |
| 3.649         | 5.0   | 2637  | 3.6899          | 0.0868   |
| 3.6459        | 6.0   | 3165  | 3.6261          | 0.1077   |
| 3.5103        | 7.0   | 3692  | 3.5303          | 0.1216   |
| 3.4177        | 8.0   | 4220  | 3.4234          | 0.1503   |
| 3.3008        | 9.0   | 4747  | 3.3969          | 0.1586   |
| 3.0881        | 10.0  | 5275  | 3.2262          | 0.1993   |
| 2.9312        | 11.0  | 5802  | 3.1606          | 0.2214   |
| 2.7669        | 12.0  | 6330  | 3.1171          | 0.2364   |
| 2.5412        | 13.0  | 6857  | 3.1180          | 0.2495   |
| 2.4121        | 14.0  | 7385  | 3.1714          | 0.2458   |
| 2.1346        | 15.0  | 7912  | 3.2153          | 0.2587   |
| 2.0515        | 16.0  | 8440  | 3.3048          | 0.2564   |
| 1.7885        | 17.0  | 8967  | 3.3968          | 0.2558   |
| 1.6461        | 18.0  | 9495  | 3.5184          | 0.2511   |
| 1.4339        | 19.0  | 10022 | 3.7439          | 0.2549   |
| 1.2975        | 20.0  | 10550 | 3.8629          | 0.2549   |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2