pytorch tensorboard data2vec-audio automatic-speech-recognition dataset:common_voice transformers generated_from_trainer license:apache-2.0 model-index
---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: data2vec-large-uk
  results: []
---

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# data2vec-large-uk

This model is a fine-tuned version of [facebook/data2vec-audio-large-960h](https://huggingface.co/facebook/data2vec-audio-large-960h) on the common_voice dataset.
It achieves the following results on the evaluation set:
- eval_loss: 0.3472
- eval_wer: 0.3410
- eval_cer: 0.0832
- eval_runtime: 231.0008
- eval_samples_per_second: 25.108
- eval_steps_per_second: 3.139
- epoch: 33.06
- step: 20400

## 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: 6
- total_train_batch_size: 48
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 100
- mixed_precision_training: Native AMP

### Framework versions

- Transformers 4.18.0
- Pytorch 1.11.0
- Datasets 1.18.3
- Tokenizers 0.12.1
