---
license:
- other
- apache-2.0
base_model: TiMauzi/wav2vec2-large-xls-r-300m-hsb
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-xls-r-300m-dsb-with-hsb-pretraining
  results: []
language:
- dsb
datasets:
- mozilla-foundation/common_voice_11_0
metrics:
- wer
---

<!-- 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-dsb-with-hsb-pretraining

This model continued training from a model based on [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) fine-tuned on Upper Sorbian common_voice_11_0 dataset.
Hence, it is a fine-tuned version of [TiMauzi/wav2vec2-large-xls-r-300m-hsb](https://huggingface.co/TiMauzi/wav2vec2-large-xls-r-300m-hsb) on the dataset ["maminorěcna dolnoserbšćina"](https://dolnoserbski.de/dobes/?r%C4%9Bc=dsb) (native Lower Sorbian corpus). The rights on this dataset are reserved by the Institute for the Study of the Language, History and Culture of the Lusatian Sorbs/Wends and Comparative Minority Research. In case of any copyright issues, feel free to contact me so I can take this model offline.


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 12
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 36
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 50
- num_epochs: 1

### Training results

| Step | Training Loss | Validation Loss | Wer |
|---|---|---|---|
| 200 | 1.603500 | 1.160496 | 0.542402 |
| 400 | 0.826000 | 1.221802 | 0.542985 |
| 600 | 0.522700 | 1.348839 | 0.467980 |
| 800 | 0.401200 | 1.178484 | 0.443043 |
| 1000 | 0.280700 | 1.428626 | 0.438385 |
| 1200 | 0.216700 | 1.300642 | 0.433631 |

### Framework versions

- Transformers 4.32.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3