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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
base_model: facebook/wav2vec2-xls-r-300m
model-index:
- name: wav2vec2-large-xls-r-300m-dansk-CV-80
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-dansk-CV-80
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) for Danish, using the [mozilla-foundation/common_voice_8_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0) dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.6394
- eval_wer: 0.3682
- eval_runtime: 104.0466
- eval_samples_per_second: 13.359
- eval_steps_per_second: 1.672
- epoch: 21.28
- step: 2000
## Model description
ASR Danish model
## Intended uses & limitations
More information needed
## Training and evaluation data
Danish subset of [mozilla-foundation/common_voice_8_0](https://huggingface.co/datasets/mozilla-foundation/common_voice_8_0)
## Training procedure
### Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Framework versions
- Transformers 4.16.1
- Pytorch 1.10.0+cu111
- Datasets 1.18.2
- Tokenizers 0.11.0