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---
license: apache-2.0
base_model: facebook/hubert-base-ls960
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: ckpts
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. -->
# ckpts
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: 0.2847
- Accuracy: 0.9394
## 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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.4293 | 2.2422 | 500 | 0.4459 | 0.8788 |
| 0.2063 | 4.4843 | 1000 | 0.2847 | 0.9394 |
| 0.1392 | 6.7265 | 1500 | 0.3088 | 0.9394 |
| 0.1434 | 8.9686 | 2000 | 0.3495 | 0.9444 |
| 0.097 | 11.2108 | 2500 | 0.3493 | 0.9394 |
### Framework versions
- Transformers 4.40.0.dev0
- Pytorch 2.1.2
- Datasets 2.18.1.dev0
- Tokenizers 0.15.2
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