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-V2-5
  results: []
---

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# hubert-large-ls960-ft-V2-5

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: 0.5760
- Wer: 0.1085
- Per: 0.0892

## 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    |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|
| 19.707        | 1.0   | 82   | 3.5254          | 1.0    | 1.0    |
| 3.4906        | 2.0   | 164  | 3.2483          | 1.0    | 1.0    |
| 3.233         | 3.0   | 246  | 3.1368          | 1.0    | 1.0    |
| 3.0468        | 4.0   | 328  | 2.9600          | 1.0    | 1.0    |
| 2.6751        | 5.0   | 410  | 2.3348          | 1.0    | 1.0    |
| 2.0881        | 6.0   | 492  | 1.7351          | 0.8568 | 0.8726 |
| 1.4875        | 7.0   | 574  | 1.2264          | 0.6059 | 0.6134 |
| 1.0922        | 8.0   | 656  | 0.9666          | 0.4068 | 0.3972 |
| 0.8148        | 9.0   | 738  | 0.7746          | 0.3249 | 0.3138 |
| 0.6332        | 10.0  | 820  | 0.6755          | 0.2477 | 0.2313 |
| 0.4797        | 11.0  | 902  | 0.6262          | 0.1612 | 0.1410 |
| 0.3807        | 12.0  | 984  | 0.5765          | 0.1384 | 0.1172 |
| 0.3195        | 13.0  | 1066 | 0.5666          | 0.1191 | 0.0992 |
| 0.2526        | 14.0  | 1148 | 0.5759          | 0.1165 | 0.0970 |
| 0.2417        | 15.0  | 1230 | 0.5460          | 0.1138 | 0.0946 |
| 0.2072        | 16.0  | 1312 | 0.5551          | 0.1095 | 0.0912 |
| 0.1881        | 17.0  | 1394 | 0.5745          | 0.1102 | 0.0917 |
| 0.1888        | 18.0  | 1476 | 0.5731          | 0.1094 | 0.0907 |
| 0.202         | 19.0  | 1558 | 0.5774          | 0.1081 | 0.0893 |
| 0.1813        | 20.0  | 1640 | 0.5760          | 0.1085 | 0.0892 |


### Framework versions

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