---
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
  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

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: 1.9150
- Accuracy: 0.7349

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 4.0503        | 1.0   | 527   | 3.9739          | 0.0814   |
| 3.8351        | 2.0   | 1055  | 3.7950          | 0.0837   |
| 3.7053        | 3.0   | 1582  | 3.6592          | 0.1081   |
| 3.4539        | 4.0   | 2110  | 3.3374          | 0.1772   |
| 2.657         | 5.0   | 2637  | 2.5832          | 0.3443   |
| 2.1356        | 6.0   | 3165  | 2.0006          | 0.4873   |
| 1.7409        | 7.0   | 3692  | 1.7459          | 0.5627   |
| 1.4391        | 8.0   | 4220  | 1.6168          | 0.6104   |
| 1.1336        | 9.0   | 4747  | 1.5041          | 0.6489   |
| 1.0151        | 10.0  | 5275  | 1.4378          | 0.6786   |
| 0.8624        | 11.0  | 5802  | 1.4653          | 0.6880   |
| 0.6583        | 12.0  | 6330  | 1.4319          | 0.6998   |
| 0.7089        | 13.0  | 6857  | 1.4993          | 0.7095   |
| 0.6454        | 14.0  | 7385  | 1.5267          | 0.7036   |
| 0.5424        | 15.0  | 7912  | 1.5672          | 0.7152   |
| 0.425         | 16.0  | 8440  | 1.6051          | 0.7159   |
| 0.4016        | 17.0  | 8967  | 1.6342          | 0.7173   |
| 0.3563        | 18.0  | 9495  | 1.7061          | 0.7110   |
| 0.367         | 19.0  | 10022 | 1.6884          | 0.7177   |
| 0.3511        | 20.0  | 10550 | 1.7300          | 0.7154   |
| 0.3573        | 21.0  | 11077 | 1.7361          | 0.7230   |
| 0.2533        | 22.0  | 11605 | 1.7119          | 0.7279   |
| 0.2029        | 23.0  | 12132 | 1.7801          | 0.7279   |
| 0.3279        | 24.0  | 12660 | 1.8096          | 0.7324   |
| 0.2164        | 25.0  | 13187 | 1.8916          | 0.7237   |
| 0.2092        | 26.0  | 13715 | 1.8348          | 0.7274   |
| 0.1757        | 27.0  | 14242 | 1.8824          | 0.7286   |
| 0.2584        | 28.0  | 14770 | 1.9150          | 0.7349   |
| 0.1605        | 29.0  | 15297 | 1.9417          | 0.7305   |
| 0.1815        | 30.0  | 15825 | 1.8939          | 0.7309   |
| 0.1749        | 31.0  | 16352 | 1.9729          | 0.7327   |
| 0.1628        | 32.0  | 16880 | 1.9796          | 0.7275   |
| 0.1369        | 33.0  | 17407 | 2.0156          | 0.7322   |


### Framework versions

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