transformers safetensors hubert automatic-speech-recognition generated_from_trainer base_model:facebook/hubert-large-ls960-ft license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/hubert-large-ls960-ft
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: hubert-large-ls960-ft-V2-10
  results: []
---

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# hubert-large-ls960-ft-V2-10

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: 0.4727
- Wer: 0.0628
- Per: 0.0490

## 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: 2
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 14.6873       | 1.0   | 164  | 3.2286          | 1.0    | 1.0    |
| 3.2356        | 2.0   | 328  | 3.1024          | 1.0    | 1.0    |
| 2.6803        | 3.0   | 492  | 1.9833          | 0.9224 | 0.9382 |
| 1.5141        | 4.0   | 656  | 1.1059          | 0.4099 | 0.3923 |
| 0.7862        | 5.0   | 820  | 0.6129          | 0.1587 | 0.1357 |
| 0.4004        | 6.0   | 984  | 0.4939          | 0.0939 | 0.0748 |
| 0.2791        | 7.0   | 1148 | 0.4888          | 0.0815 | 0.0646 |
| 0.2168        | 8.0   | 1312 | 0.5083          | 0.0830 | 0.0662 |
| 0.1726        | 9.0   | 1476 | 0.4748          | 0.0749 | 0.0596 |
| 0.1412        | 10.0  | 1640 | 0.4955          | 0.0742 | 0.0575 |
| 0.1156        | 11.0  | 1804 | 0.4986          | 0.0715 | 0.0564 |
| 0.1321        | 12.0  | 1968 | 0.5101          | 0.0703 | 0.0552 |
| 0.103         | 13.0  | 2132 | 0.4728          | 0.0668 | 0.0527 |
| 0.0772        | 14.0  | 2296 | 0.4832          | 0.0649 | 0.0509 |
| 0.0858        | 15.0  | 2460 | 0.4830          | 0.0649 | 0.0505 |
| 0.0874        | 16.0  | 2624 | 0.4697          | 0.0642 | 0.0509 |
| 0.0784        | 17.0  | 2788 | 0.4499          | 0.0652 | 0.0516 |
| 0.0703        | 18.0  | 2952 | 0.4699          | 0.0638 | 0.0500 |
| 0.062         | 19.0  | 3116 | 0.4757          | 0.0634 | 0.0496 |
| 0.0588        | 20.0  | 3280 | 0.4727          | 0.0628 | 0.0490 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.0
