---
license: apache-2.0
base_model: DewiBrynJones/wav2vec2-xlsr-53-ft-btb-cv-cy
tags:
- automatic-speech-recognition
- ./data-configs/btb.json
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-btb-cv-ft-btb-cy-cand
  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-btb-cv-ft-btb-cy-cand

This model is a fine-tuned version of [DewiBrynJones/wav2vec2-xlsr-53-ft-btb-cv-cy](https://huggingface.co./DewiBrynJones/wav2vec2-xlsr-53-ft-btb-cv-cy) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.3402

## 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: 4
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- training_steps: 10000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Wer    |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| No log        | 0.0215 | 200   | inf             | 0.5592 |
| No log        | 0.0429 | 400   | inf             | 0.4289 |
| 2.1964        | 0.0644 | 600   | inf             | 0.4374 |
| 2.1964        | 0.0858 | 800   | inf             | 0.4944 |
| 0.8327        | 0.1073 | 1000  | inf             | 0.5150 |
| 0.8327        | 0.1287 | 1200  | inf             | 0.5634 |
| 0.8327        | 0.1502 | 1400  | inf             | 0.5355 |
| 0.91          | 0.1716 | 1600  | inf             | 0.5152 |
| 0.91          | 0.1931 | 1800  | inf             | 0.5595 |
| 0.8721        | 0.2145 | 2000  | inf             | 0.5057 |
| 0.8721        | 0.2360 | 2200  | inf             | 0.5041 |
| 0.8721        | 0.2574 | 2400  | inf             | 0.5146 |
| 0.8218        | 0.2789 | 2600  | inf             | 0.5018 |
| 0.8218        | 0.3003 | 2800  | inf             | 0.5091 |
| 0.8469        | 0.3218 | 3000  | inf             | 0.5037 |
| 0.8469        | 0.3432 | 3200  | inf             | 0.4703 |
| 0.8469        | 0.3647 | 3400  | inf             | 0.4795 |
| 0.8142        | 0.3861 | 3600  | inf             | 0.4714 |
| 0.8142        | 0.4076 | 3800  | inf             | 0.4554 |
| 0.8085        | 0.4290 | 4000  | inf             | 0.4506 |
| 0.8085        | 0.4505 | 4200  | inf             | 0.4458 |
| 0.8085        | 0.4720 | 4400  | inf             | 0.4367 |
| 0.7802        | 0.4934 | 4600  | inf             | 0.4401 |
| 0.7802        | 0.5149 | 4800  | inf             | 0.4334 |
| 0.7493        | 0.5363 | 5000  | inf             | 0.4224 |
| 0.7493        | 0.5578 | 5200  | inf             | 0.4328 |
| 0.7493        | 0.5792 | 5400  | inf             | 0.4176 |
| 0.7668        | 0.6007 | 5600  | inf             | 0.4183 |
| 0.7668        | 0.6221 | 5800  | inf             | 0.4030 |
| 0.6999        | 0.6436 | 6000  | inf             | 0.4125 |
| 0.6999        | 0.6650 | 6200  | inf             | 0.4076 |
| 0.6999        | 0.6865 | 6400  | inf             | 0.3917 |
| 0.6918        | 0.7079 | 6600  | inf             | 0.4004 |
| 0.6918        | 0.7294 | 6800  | inf             | 0.3865 |
| 0.6888        | 0.7508 | 7000  | inf             | 0.3785 |
| 0.6888        | 0.7723 | 7200  | inf             | 0.3824 |
| 0.6888        | 0.7937 | 7400  | inf             | 0.3743 |
| 0.646         | 0.8152 | 7600  | inf             | 0.3673 |
| 0.646         | 0.8366 | 7800  | inf             | 0.3667 |
| 0.6324        | 0.8581 | 8000  | inf             | 0.3662 |
| 0.6324        | 0.8795 | 8200  | inf             | 0.3601 |
| 0.6324        | 0.9010 | 8400  | inf             | 0.3535 |
| 0.6221        | 0.9224 | 8600  | inf             | 0.3526 |
| 0.6221        | 0.9439 | 8800  | inf             | 0.3487 |
| 0.6215        | 0.9654 | 9000  | inf             | 0.3481 |
| 0.6215        | 0.9868 | 9200  | inf             | 0.3447 |
| 0.6215        | 1.0083 | 9400  | inf             | 0.3410 |
| 0.5603        | 1.0297 | 9600  | inf             | 0.3405 |
| 0.5603        | 1.0512 | 9800  | inf             | 0.3412 |
| 0.5284        | 1.0726 | 10000 | inf             | 0.3402 |


### Framework versions

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