---
library_name: transformers
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-large-timit-upsample-4-50
  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-large-timit-upsample-4-50

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1708
- Wer: 0.7941

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch   | Step | Validation Loss | Wer    |
|:-------------:|:-------:|:----:|:---------------:|:------:|
| 0.5553        | 2.4752  | 500  | 0.4724          | 0.9855 |
| 0.3331        | 4.9505  | 1000 | 0.2739          | 0.9504 |
| 0.2707        | 7.4257  | 1500 | 0.2362          | 0.9635 |
| 0.2411        | 9.9010  | 2000 | 0.2191          | 0.9122 |
| 0.2246        | 12.3762 | 2500 | 0.2068          | 0.8596 |
| 0.2088        | 14.8515 | 3000 | 0.1971          | 0.8365 |
| 0.1951        | 17.3267 | 3500 | 0.1918          | 0.8261 |
| 0.187         | 19.8020 | 4000 | 0.1864          | 0.8227 |
| 0.1769        | 22.2772 | 4500 | 0.1851          | 0.8210 |
| 0.1728        | 24.7525 | 5000 | 0.1811          | 0.8250 |
| 0.1682        | 27.2277 | 5500 | 0.1730          | 0.8135 |
| 0.1662        | 29.7030 | 6000 | 0.1708          | 0.7941 |


### Framework versions

- Transformers 4.51.3
- Pytorch 2.2.1
- Datasets 3.6.0
- Tokenizers 0.21.1