---
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert_large_528_10
  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_528_10

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: 0.7757
- Wer: 0.2425

## 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: 0.0001
- train_batch_size: 2
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 8
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.1878        | 0.3378 | 100  | 0.9689          | 0.3245 |
| 1.2219        | 0.6757 | 200  | 0.8869          | 0.2887 |
| 1.4146        | 1.0135 | 300  | 0.7800          | 0.2827 |
| 0.9472        | 1.3514 | 400  | 0.7899          | 0.2829 |
| 0.9176        | 1.6892 | 500  | 0.8345          | 0.2773 |
| 1.0975        | 2.0270 | 600  | 0.8103          | 0.2704 |
| 1.0267        | 2.3649 | 700  | 0.8043          | 0.2661 |
| 0.9401        | 2.7027 | 800  | 0.8001          | 0.2648 |
| 0.9752        | 3.0405 | 900  | 0.8112          | 0.2595 |
| 0.9301        | 3.3784 | 1000 | 0.8174          | 0.2593 |
| 0.7361        | 3.7162 | 1100 | 0.8497          | 0.2567 |
| 0.9846        | 4.0541 | 1200 | 0.8002          | 0.2513 |
| 0.9202        | 4.3919 | 1300 | 0.7937          | 0.2524 |
| 0.7069        | 4.7297 | 1400 | 0.8582          | 0.2448 |
| 1.0649        | 5.0676 | 1500 | 0.7993          | 0.2449 |
| 0.6096        | 5.4054 | 1600 | 0.8183          | 0.2442 |
| 0.6876        | 5.7432 | 1700 | 0.8041          | 0.2426 |
| 0.7614        | 6.0811 | 1800 | 0.8133          | 0.2454 |
| 0.572         | 6.4189 | 1900 | 0.7747          | 0.2441 |
| 0.5909        | 6.7568 | 2000 | 0.7610          | 0.2447 |
| 0.562         | 7.0946 | 2100 | 0.7784          | 0.2450 |
| 0.5979        | 7.4324 | 2200 | 0.7675          | 0.2427 |
| 0.541         | 7.7703 | 2300 | 0.7757          | 0.2425 |


### Framework versions

- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1