---
license: apache-2.0
base_model: ctl/wav2vec2-large-xlsr-cantonese
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-zhhk
  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. -->

# wav2vec2-large-xls-r-300m-zhhk

This model is a fine-tuned version of [ctl/wav2vec2-large-xlsr-cantonese](https://huggingface.co/ctl/wav2vec2-large-xlsr-cantonese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 4.6213
- Cer: 0.7864

## 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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 30
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.3317        | 1.35  | 400  | 4.5373          | 0.7915 |
| 0.3303        | 2.71  | 800  | 4.5198          | 0.7915 |
| 0.3288        | 4.06  | 1200 | 4.8663          | 0.8504 |
| 0.2901        | 5.41  | 1600 | 4.6080          | 0.8198 |
| 0.2819        | 6.77  | 2000 | 4.4941          | 0.7316 |
| 0.2629        | 8.12  | 2400 | 4.6927          | 0.8021 |
| 0.2363        | 9.48  | 2800 | 4.8796          | 0.8701 |
| 0.2205        | 10.83 | 3200 | 4.6338          | 0.8087 |
| 0.2171        | 12.18 | 3600 | 4.5740          | 0.7562 |
| 0.1875        | 13.54 | 4000 | 4.6072          | 0.7992 |
| 0.1824        | 14.89 | 4400 | 4.6546          | 0.7669 |
| 0.178         | 16.24 | 4800 | 4.6410          | 0.7961 |
| 0.1644        | 17.6  | 5200 | 4.7306          | 0.8236 |
| 0.155         | 18.95 | 5600 | 4.6632          | 0.7900 |
| 0.1396        | 20.3  | 6000 | 4.6239          | 0.8015 |
| 0.1411        | 21.66 | 6400 | 4.6007          | 0.7793 |
| 0.13          | 23.01 | 6800 | 4.5354          | 0.7475 |
| 0.1232        | 24.37 | 7200 | 4.6229          | 0.7600 |
| 0.1239        | 25.72 | 7600 | 4.6382          | 0.7727 |
| 0.1322        | 27.07 | 8000 | 4.6734          | 0.7902 |
| 0.1338        | 28.43 | 8400 | 4.6536          | 0.7861 |
| 0.1353        | 29.78 | 8800 | 4.6213          | 0.7864 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.15.0
- Tokenizers 0.15.0