tensorboard safetensors generated_from_trainer base_model:facebook/hubert-large-ls960-ft license:apache-2.0 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
  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-ls960-ft

This model is a fine-tuned version of [facebook/hubert-large-ls960-ft](https://huggingface.co/facebook/hubert-large-ls960-ft) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.4850
- Wer: 0.7884
- Per: 0.7945

## 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
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Per    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 14.5096       | 1.0   | 1637  | 3.3563          | 1.0    | 1.0    |
| 3.3754        | 2.0   | 3274  | 3.3135          | 1.0    | 1.0    |
| 3.3037        | 3.0   | 4911  | 3.2654          | 1.0    | 1.0    |
| 3.2641        | 4.0   | 6548  | 3.2260          | 1.0    | 1.0    |
| 3.1723        | 5.0   | 8185  | 3.1158          | 0.9975 | 0.9980 |
| 3.0864        | 6.0   | 9822  | 3.0251          | 0.9105 | 0.9234 |
| 3.0205        | 7.0   | 11459 | 2.9357          | 0.8957 | 0.9068 |
| 2.9474        | 8.0   | 13096 | 2.8523          | 0.8456 | 0.8528 |
| 2.883         | 9.0   | 14733 | 2.7752          | 0.8260 | 0.8323 |
| 2.8246        | 10.0  | 16370 | 2.7173          | 0.8138 | 0.8202 |
| 2.7959        | 11.0  | 18007 | 2.6877          | 0.8074 | 0.8139 |
| 2.7595        | 12.0  | 19644 | 2.6459          | 0.8131 | 0.8224 |
| 2.7335        | 13.0  | 21281 | 2.6208          | 0.8050 | 0.8120 |
| 2.7014        | 14.0  | 22918 | 2.5800          | 0.7986 | 0.8054 |
| 2.6792        | 15.0  | 24555 | 2.5604          | 0.7989 | 0.8058 |
| 2.6539        | 16.0  | 26192 | 2.5289          | 0.7929 | 0.7985 |
| 2.6316        | 17.0  | 27829 | 2.5119          | 0.7943 | 0.8018 |
| 2.6212        | 18.0  | 29466 | 2.4965          | 0.7931 | 0.8005 |
| 2.6114        | 19.0  | 31103 | 2.4890          | 0.7894 | 0.7959 |
| 2.6028        | 20.0  | 32740 | 2.4850          | 0.7884 | 0.7945 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
