transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer base_model:ctl/wav2vec2-large-xlsr-cantonese license:apache-2.0 endpoints_compatible region:us
---
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: []
---

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# 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: 1.5094
- Cer: 0.3540

## 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: 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: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.6545        | 0.32  | 400  | 1.6247          | 0.3646 |
| 0.621         | 0.64  | 800  | 1.5691          | 0.3588 |
| 0.8621        | 0.96  | 1200 | 1.5094          | 0.3540 |


### Framework versions

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