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---
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