---
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: 0.3289

## 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
- 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        | 0.0772 | 200  | inf             | 1.0    |
| No log        | 0.1544 | 400  | inf             | 0.9938 |
| 3.9317        | 0.2317 | 600  | inf             | 0.7576 |
| 3.9317        | 0.3089 | 800  | inf             | 0.6942 |
| 0.9699        | 0.3861 | 1000 | inf             | 0.5763 |
| 0.9699        | 0.4633 | 1200 | inf             | 0.5519 |
| 0.9699        | 0.5405 | 1400 | inf             | 0.5174 |
| 0.8031        | 0.6178 | 1600 | inf             | 0.5338 |
| 0.8031        | 0.6950 | 1800 | inf             | 0.4777 |
| 0.7169        | 0.7722 | 2000 | inf             | 0.4504 |
| 0.7169        | 0.8494 | 2200 | inf             | 0.4500 |
| 0.7169        | 0.9266 | 2400 | inf             | 0.4432 |
| 0.6687        | 1.0039 | 2600 | inf             | 0.4176 |
| 0.6687        | 1.0811 | 2800 | inf             | 0.4054 |
| 0.5609        | 1.1583 | 3000 | inf             | 0.4009 |
| 0.5609        | 1.2355 | 3200 | inf             | 0.4023 |
| 0.5609        | 1.3127 | 3400 | inf             | 0.3919 |
| 0.5324        | 1.3900 | 3600 | inf             | 0.3795 |
| 0.5324        | 1.4672 | 3800 | inf             | 0.3752 |
| 0.5196        | 1.5444 | 4000 | inf             | 0.3662 |
| 0.5196        | 1.6216 | 4200 | inf             | 0.3703 |
| 0.5196        | 1.6988 | 4400 | inf             | 0.3614 |
| 0.4967        | 1.7761 | 4600 | inf             | 0.3530 |
| 0.4967        | 1.8533 | 4800 | inf             | 0.3481 |
| 0.4735        | 1.9305 | 5000 | inf             | 0.3506 |
| 0.4735        | 2.0077 | 5200 | inf             | 0.3432 |
| 0.4735        | 2.0849 | 5400 | inf             | 0.3369 |
| 0.4244        | 2.1622 | 5600 | inf             | 0.3296 |
| 0.4244        | 2.2394 | 5800 | inf             | 0.3295 |
| 0.3674        | 2.3166 | 6000 | inf             | 0.3289 |


### Framework versions

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