---
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-frz
  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-frz

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: 3.0889
- Accuracy: 0.4598

## 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 |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 3.6605        | 1.0   | 527   | 3.6385          | 0.1020   |
| 3.6135        | 2.0   | 1055  | 3.5710          | 0.1200   |
| 3.4222        | 3.0   | 1582  | 3.3394          | 0.1738   |
| 3.1948        | 4.0   | 2110  | 3.2132          | 0.2052   |
| 2.8791        | 5.0   | 2637  | 2.9508          | 0.2581   |
| 2.7807        | 6.0   | 3165  | 2.7201          | 0.3109   |
| 2.4647        | 7.0   | 3692  | 2.6056          | 0.3393   |
| 2.3009        | 8.0   | 4220  | 2.4893          | 0.3816   |
| 2.0953        | 9.0   | 4747  | 2.4874          | 0.3902   |
| 1.8074        | 10.0  | 5275  | 2.4705          | 0.4035   |
| 1.8209        | 11.0  | 5802  | 2.4465          | 0.4177   |
| 1.4822        | 12.0  | 6330  | 2.5310          | 0.4228   |
| 1.426         | 13.0  | 6857  | 2.5097          | 0.4305   |
| 1.2877        | 14.0  | 7385  | 2.5365          | 0.4368   |
| 1.0833        | 15.0  | 7912  | 2.5874          | 0.4404   |
| 1.0709        | 16.0  | 8440  | 2.6478          | 0.4373   |
| 0.8176        | 17.0  | 8967  | 2.7096          | 0.4409   |
| 0.803         | 18.0  | 9495  | 2.7965          | 0.4491   |
| 0.6678        | 19.0  | 10022 | 2.9335          | 0.4470   |
| 0.7066        | 20.0  | 10550 | 3.0013          | 0.4408   |
| 0.5935        | 21.0  | 11077 | 2.9613          | 0.4544   |
| 0.5703        | 22.0  | 11605 | 2.9915          | 0.4534   |
| 0.5           | 23.0  | 12132 | 3.0625          | 0.4556   |
| 0.55          | 24.0  | 12660 | 3.0889          | 0.4598   |
| 0.3977        | 25.0  | 13187 | 3.1962          | 0.4551   |
| 0.4578        | 26.0  | 13715 | 3.2863          | 0.4574   |
| 0.3343        | 27.0  | 14242 | 3.3401          | 0.4531   |
| 0.4414        | 28.0  | 14770 | 3.3229          | 0.4557   |
| 0.2551        | 29.0  | 15297 | 3.4294          | 0.4567   |


### Framework versions

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