---
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-wt_init
  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-wt_init

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: 3.1377
- Accuracy: 0.4604

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.9613        | 1.0   | 527   | 3.8944          | 0.0803   |
| 3.7817        | 2.0   | 1055  | 3.7275          | 0.0910   |
| 3.6357        | 3.0   | 1582  | 3.5410          | 0.1308   |
| 3.4527        | 4.0   | 2110  | 3.3426          | 0.1676   |
| 3.0715        | 5.0   | 2637  | 3.0751          | 0.2331   |
| 2.9153        | 6.0   | 3165  | 2.8168          | 0.2969   |
| 2.5333        | 7.0   | 3692  | 2.6229          | 0.3375   |
| 2.3807        | 8.0   | 4220  | 2.5673          | 0.3620   |
| 2.181         | 9.0   | 4747  | 2.4933          | 0.3835   |
| 1.9118        | 10.0  | 5275  | 2.4411          | 0.4046   |
| 1.9015        | 11.0  | 5802  | 2.4254          | 0.4126   |
| 1.5811        | 12.0  | 6330  | 2.4216          | 0.4275   |
| 1.491         | 13.0  | 6857  | 2.4833          | 0.4284   |
| 1.3697        | 14.0  | 7385  | 2.5243          | 0.4368   |
| 1.1232        | 15.0  | 7912  | 2.5944          | 0.4309   |
| 1.1071        | 16.0  | 8440  | 2.6475          | 0.4317   |
| 0.9439        | 17.0  | 8967  | 2.6379          | 0.4449   |
| 0.917         | 18.0  | 9495  | 2.7438          | 0.4468   |
| 0.7628        | 19.0  | 10022 | 2.7671          | 0.4513   |
| 0.7642        | 20.0  | 10550 | 2.8993          | 0.4418   |
| 0.6716        | 21.0  | 11077 | 2.9354          | 0.4472   |
| 0.6166        | 22.0  | 11605 | 2.9961          | 0.4510   |
| 0.4819        | 23.0  | 12132 | 3.0959          | 0.4451   |
| 0.5903        | 24.0  | 12660 | 3.0542          | 0.4557   |
| 0.515         | 25.0  | 13187 | 3.0723          | 0.4589   |
| 0.518         | 26.0  | 13715 | 3.1377          | 0.4604   |
| 0.3902        | 27.0  | 14242 | 3.2230          | 0.4524   |
| 0.4825        | 28.0  | 14770 | 3.2925          | 0.4583   |
| 0.29          | 29.0  | 15297 | 3.4027          | 0.4498   |
| 0.2789        | 30.0  | 15825 | 3.3573          | 0.4598   |
| 0.3202        | 31.0  | 16352 | 3.4381          | 0.4542   |


### Framework versions

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