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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-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
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