transformers tensorboard safetensors wav2vec2 automatic-speech-recognition generated_from_trainer dataset:common_voice_6_1 base_model:facebook/wav2vec2-large-xlsr-53 license:apache-2.0 model-index endpoints_compatible region:us
---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_6_1
metrics:
- wer
model-index:
- name: wav2vec2-large-morrnla-ar-colab
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: common_voice_6_1
      type: common_voice_6_1
      config: ar
      split: test[10:20]
      args: ar
    metrics:
    - name: Wer
      type: wer
      value: 1.0
---

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# wav2vec2-large-morrnla-ar-colab

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_6_1 dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5524
- Wer: 1.0

## 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: 0.0003
- 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: 20
- num_epochs: 20
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:---:|
| 16.4983       | 3.33  | 10   | 23.6467         | 1.0 |
| 8.0393        | 6.67  | 20   | 7.4047          | 1.0 |
| 4.2297        | 10.0  | 30   | 4.1771          | 1.0 |
| 3.6003        | 13.33 | 40   | 3.8565          | 1.0 |
| 3.4788        | 16.67 | 50   | 3.5921          | 1.0 |
| 3.4111        | 20.0  | 60   | 3.5524          | 1.0 |


### Framework versions

- Transformers 4.36.0.dev0
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
