---
language:
- cy
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- python/custom_common_voice.py
- generated_from_trainer
datasets:
- custom_common_voice
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-ccv-en-cy
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: PYTHON/CUSTOM_COMMON_VOICE.PY - CY
      type: custom_common_voice
      config: cy
      split: validation
      args: 'Config: cy, Training split: train, Eval split: validation'
    metrics:
    - name: Wer
      type: wer
      value: 0.21777283505046477
---

<!-- 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-xlsr-53-ft-ccv-en-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the PYTHON/CUSTOM_COMMON_VOICE.PY - CY dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2909
- Wer: 0.2178

## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 9000

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.8377        | 0.25  | 500  | 1.2190          | 0.8569 |
| 0.9829        | 0.51  | 1000 | 0.5585          | 0.4701 |
| 0.45          | 0.76  | 1500 | 0.4735          | 0.3901 |
| 0.3151        | 1.01  | 2000 | 0.4125          | 0.3418 |
| 0.2524        | 1.26  | 2500 | 0.3831          | 0.3117 |
| 0.243         | 1.52  | 3000 | 0.3661          | 0.3078 |
| 0.2341        | 1.77  | 3500 | 0.3489          | 0.2883 |
| 0.211         | 2.02  | 4000 | 0.3500          | 0.2738 |
| 0.1702        | 2.27  | 4500 | 0.3459          | 0.2704 |
| 0.1634        | 2.53  | 5000 | 0.3305          | 0.2583 |
| 0.1608        | 2.78  | 5500 | 0.3137          | 0.2479 |
| 0.1481        | 3.03  | 6000 | 0.3288          | 0.2562 |
| 0.1216        | 3.28  | 6500 | 0.3174          | 0.2446 |
| 0.1181        | 3.54  | 7000 | 0.3000          | 0.2325 |
| 0.1143        | 3.79  | 7500 | 0.2929          | 0.2326 |
| 0.1049        | 4.04  | 8000 | 0.2921          | 0.2218 |
| 0.0913        | 4.29  | 8500 | 0.2968          | 0.2208 |
| 0.0883        | 4.55  | 9000 | 0.2909          | 0.2178 |


### Framework versions

- Transformers 4.33.3
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3