---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- DewiBrynJones/banc-trawsgrifiadau-bangor-clean-with-ccv
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-btb-ccv-cy
  results: []
---

<!-- 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-btb-ccv-cy

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the DEWIBRYNJONES/BANC-TRAWSGRIFIADAU-BANGOR-CLEAN-WITH-CCV - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4942
- Wer: 0.3917

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 300
- training_steps: 3000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.0672 | 200  | 2.9830          | 1.0    |
| No log        | 0.1344 | 400  | 1.5613          | 0.9658 |
| 3.6118        | 0.2016 | 600  | 1.0701          | 0.7649 |
| 3.6118        | 0.2688 | 800  | 0.8868          | 0.6947 |
| 0.9333        | 0.3360 | 1000 | 0.7680          | 0.6071 |
| 0.9333        | 0.4032 | 1200 | 0.7224          | 0.5454 |
| 0.9333        | 0.4704 | 1400 | 0.6733          | 0.5122 |
| 0.7446        | 0.5376 | 1600 | 0.6437          | 0.4966 |
| 0.7446        | 0.6048 | 1800 | 0.6064          | 0.4774 |
| 0.6579        | 0.6720 | 2000 | 0.5674          | 0.4461 |
| 0.6579        | 0.7392 | 2200 | 0.5556          | 0.4325 |
| 0.6579        | 0.8065 | 2400 | 0.5264          | 0.4180 |
| 0.5823        | 0.8737 | 2600 | 0.5130          | 0.4022 |
| 0.5823        | 0.9409 | 2800 | 0.4982          | 0.3936 |
| 0.5426        | 1.0081 | 3000 | 0.4942          | 0.3917 |


### Framework versions

- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1