---
license: apache-2.0
tags:
- automatic-speech-recognition
- techiaith/banc-trawsgrifiadau-bangor
- generated_from_trainer
datasets:
- banc-trawsgrifiadau-bangor
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-ft-btb
  results:
  - task:
      name: Automatic Speech Recognition
      type: automatic-speech-recognition
    dataset:
      name: TECHIAITH/BANC-TRAWSGRIFIADAU-BANGOR - NA
      type: banc-trawsgrifiadau-bangor
      config: default
      split: test
      args: 'Config: na, Training split: train, Eval split: test'
    metrics:
    - name: Wer
      type: wer
      value: 0.3262315072590479
language:
- cy
pipeline_tag: automatic-speech-recognition
---

<!-- 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-ft-cy-verbatim

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the 
[techiaith/banc-trawsgrifiadau-bangor](https://huggingface.co/datasets/techiaith/banc-trawsgrifiadau-bangor) dataset. 
It achieves the following results on the evaluation set:
- Loss: 0.4357
- Wer: 0.3262

## 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: 500
- num_epochs: 5.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log        | 0.21  | 100  | 3.4135          | 1.0    |
| No log        | 0.41  | 200  | 2.9521          | 1.0    |
| No log        | 0.62  | 300  | 2.3339          | 0.9365 |
| No log        | 0.83  | 400  | 1.2433          | 0.8259 |
| 3.1912        | 1.03  | 500  | 0.8614          | 0.6385 |
| 3.1912        | 1.24  | 600  | 0.7557          | 0.5612 |
| 3.1912        | 1.44  | 700  | 0.6781          | 0.5195 |
| 3.1912        | 1.65  | 800  | 0.6363          | 0.4879 |
| 3.1912        | 1.86  | 900  | 0.5959          | 0.4559 |
| 0.8237        | 2.06  | 1000 | 0.5430          | 0.4260 |
| 0.8237        | 2.27  | 1100 | 0.5293          | 0.4098 |
| 0.8237        | 2.48  | 1200 | 0.5141          | 0.4056 |
| 0.8237        | 2.68  | 1300 | 0.4879          | 0.3947 |
| 0.8237        | 2.89  | 1400 | 0.4697          | 0.3788 |
| 0.5625        | 3.1   | 1500 | 0.4748          | 0.3780 |
| 0.5625        | 3.3   | 1600 | 0.4836          | 0.3684 |
| 0.5625        | 3.51  | 1700 | 0.4796          | 0.3625 |
| 0.5625        | 3.72  | 1800 | 0.4582          | 0.3515 |
| 0.5625        | 3.92  | 1900 | 0.4395          | 0.3437 |
| 0.4267        | 4.13  | 2000 | 0.4410          | 0.3420 |
| 0.4267        | 4.33  | 2100 | 0.4467          | 0.3382 |
| 0.4267        | 4.54  | 2200 | 0.4398          | 0.3329 |
| 0.4267        | 4.75  | 2300 | 0.4383          | 0.3287 |
| 0.4267        | 4.95  | 2400 | 0.4358          | 0.3264 |


### Framework versions

- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3