---
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert_large_531
  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_531

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: 0.7843
- Wer: 0.2445

## 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

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.1649        | 0.3378 | 100  | 0.9661          | 0.3229 |
| 1.2208        | 0.6757 | 200  | 0.8651          | 0.2918 |
| 1.412         | 1.0135 | 300  | 0.7681          | 0.2915 |
| 0.9419        | 1.3514 | 400  | 0.7712          | 0.2818 |
| 0.9161        | 1.6892 | 500  | 0.8276          | 0.2776 |
| 1.0943        | 2.0270 | 600  | 0.8074          | 0.2706 |
| 1.0036        | 2.3649 | 700  | 0.7917          | 0.2691 |
| 0.9262        | 2.7027 | 800  | 0.7897          | 0.2644 |
| 0.9841        | 3.0405 | 900  | 0.8006          | 0.2590 |
| 0.9327        | 3.3784 | 1000 | 0.8068          | 0.2630 |
| 0.7249        | 3.7162 | 1100 | 0.8546          | 0.2533 |
| 0.9704        | 4.0541 | 1200 | 0.8350          | 0.2533 |
| 0.8985        | 4.3919 | 1300 | 0.8414          | 0.2478 |
| 0.6858        | 4.7297 | 1400 | 0.8533          | 0.2469 |
| 1.0581        | 5.0676 | 1500 | 0.8200          | 0.2459 |
| 0.5899        | 5.4054 | 1600 | 0.8378          | 0.2459 |
| 0.6891        | 5.7432 | 1700 | 0.8094          | 0.2478 |
| 0.7276        | 6.0811 | 1800 | 0.8326          | 0.2438 |
| 0.5738        | 6.4189 | 1900 | 0.7844          | 0.2456 |
| 0.5837        | 6.7568 | 2000 | 0.7773          | 0.2473 |
| 0.5476        | 7.0946 | 2100 | 0.7725          | 0.2488 |
| 0.6004        | 7.4324 | 2200 | 0.7693          | 0.2471 |
| 0.5391        | 7.7703 | 2300 | 0.7843          | 0.2445 |


### Framework versions

- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1