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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
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
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