transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_13_0 base_model:facebook/wav2vec2-conformer-rel-pos-large license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-conformer-rel-pos-large
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-conformer-large-cv13
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_13_0
      type: common_voice_13_0
      config: ja
      split: test[:10%]
      args: ja
    metrics:
    - name: Wer
      type: wer
      value: 0.961053330382828
---

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# wav2vec2-conformer-large-cv13

This model is a fine-tuned version of [facebook/wav2vec2-conformer-rel-pos-large](https://huggingface.co/facebook/wav2vec2-conformer-rel-pos-large) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 5.3295
- Wer: 0.9611

## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 16
- 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: 500
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 8.4756        | 1.0   | 715  | 5.7619          | 1.0    |
| 5.6554        | 2.0   | 1430 | 5.7260          | 1.0    |
| 5.4654        | 3.0   | 2146 | 5.5588          | 0.9993 |
| 5.421         | 4.0   | 2861 | 5.5970          | 0.9918 |
| 5.3141        | 5.0   | 3577 | 5.4359          | 0.9794 |
| 5.2603        | 6.0   | 4292 | 5.4187          | 0.9792 |
| 5.1834        | 7.0   | 5008 | 5.3865          | 0.9785 |
| 5.1195        | 8.0   | 5723 | 5.3875          | 0.9661 |
| 5.0788        | 9.0   | 6438 | 5.3399          | 0.9668 |
| 4.9988        | 9.99  | 7150 | 5.3295          | 0.9611 |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
