---
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: inf
- Wer: 0.5238

## 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: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 6000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log        | 0.1544 | 200  | inf             | 1.0    |
| No log        | 0.3089 | 400  | inf             | 0.8661 |
| 3.7305        | 0.4633 | 600  | inf             | 0.7040 |
| 3.7305        | 0.6178 | 800  | inf             | 0.5506 |
| 0.8464        | 0.7722 | 1000 | inf             | 0.5168 |
| 0.8464        | 0.9266 | 1200 | inf             | 0.4825 |
| 0.8464        | 1.0811 | 1400 | inf             | 0.4601 |
| 0.6629        | 1.2355 | 1600 | inf             | 0.4445 |
| 0.6629        | 1.3900 | 1800 | inf             | 0.4143 |
| 0.5655        | 1.5444 | 2000 | inf             | 0.4170 |
| 0.5655        | 1.6988 | 2200 | inf             | 0.4047 |
| 0.5655        | 1.8533 | 2400 | inf             | 0.3966 |
| 0.5524        | 2.0077 | 2600 | inf             | 0.3779 |
| 0.5524        | 2.1622 | 2800 | inf             | 0.3737 |
| 0.4773        | 2.3166 | 3000 | inf             | 0.3698 |
| 0.4773        | 2.4710 | 3200 | inf             | 0.3724 |
| 0.4773        | 2.6255 | 3400 | inf             | 0.3584 |
| 0.4694        | 2.7799 | 3600 | inf             | 0.3821 |
| 0.4694        | 2.9344 | 3800 | inf             | 0.4730 |
| 0.6537        | 3.0888 | 4000 | inf             | 0.4754 |
| 0.6537        | 3.2432 | 4200 | inf             | 0.5899 |
| 0.6537        | 3.3977 | 4400 | inf             | 0.5958 |
| 0.8238        | 3.5521 | 4600 | inf             | 0.6336 |
| 0.8238        | 3.7066 | 4800 | inf             | 0.6026 |
| 0.8682        | 3.8610 | 5000 | inf             | 0.5671 |
| 0.8682        | 4.0154 | 5200 | inf             | 0.5378 |
| 0.8682        | 4.1699 | 5400 | inf             | 0.5374 |
| 0.855         | 4.3243 | 5600 | inf             | 0.5328 |
| 0.855         | 4.4788 | 5800 | inf             | 0.5225 |
| 0.9644        | 4.6332 | 6000 | inf             | 0.5238 |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1