---
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: 0.4345
- Wer: 0.3308

## 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        | 0.0285 | 200   | 1.2522          | 0.6292 |
| No log        | 0.0570 | 400   | 0.6599          | 0.4544 |
| 2.2791        | 0.0854 | 600   | 0.6629          | 0.4395 |
| 2.2791        | 0.1139 | 800   | 0.7910          | 0.5453 |
| 0.8206        | 0.1424 | 1000  | 0.7758          | 0.5701 |
| 0.8206        | 0.1709 | 1200  | 0.8025          | 0.5783 |
| 0.8206        | 0.1994 | 1400  | 0.7715          | 0.5211 |
| 0.9068        | 0.2279 | 1600  | 0.7349          | 0.5128 |
| 0.9068        | 0.2563 | 1800  | 0.7258          | 0.5152 |
| 0.8679        | 0.2848 | 2000  | 0.7084          | 0.5216 |
| 0.8679        | 0.3133 | 2200  | 0.6904          | 0.5014 |
| 0.8679        | 0.3418 | 2400  | 0.6993          | 0.5178 |
| 0.8577        | 0.3703 | 2600  | 0.6746          | 0.4867 |
| 0.8577        | 0.3987 | 2800  | 0.6622          | 0.4963 |
| 0.7995        | 0.4272 | 3000  | 0.6793          | 0.4935 |
| 0.7995        | 0.4557 | 3200  | 0.6368          | 0.4701 |
| 0.7995        | 0.4842 | 3400  | 0.6363          | 0.4781 |
| 0.8141        | 0.5127 | 3600  | 0.6217          | 0.4656 |
| 0.8141        | 0.5412 | 3800  | 0.6418          | 0.4940 |
| 0.7953        | 0.5696 | 4000  | 0.6018          | 0.4542 |
| 0.7953        | 0.5981 | 4200  | 0.5962          | 0.4580 |
| 0.7953        | 0.6266 | 4400  | 0.5883          | 0.4459 |
| 0.7596        | 0.6551 | 4600  | 0.5788          | 0.4325 |
| 0.7596        | 0.6836 | 4800  | 0.5709          | 0.4412 |
| 0.7533        | 0.7120 | 5000  | 0.5595          | 0.4352 |
| 0.7533        | 0.7405 | 5200  | 0.5546          | 0.4232 |
| 0.7533        | 0.7690 | 5400  | 0.5545          | 0.4244 |
| 0.7591        | 0.7975 | 5600  | 0.5443          | 0.4076 |
| 0.7591        | 0.8260 | 5800  | 0.5341          | 0.4146 |
| 0.6621        | 0.8545 | 6000  | 0.5104          | 0.3955 |
| 0.6621        | 0.8829 | 6200  | 0.5139          | 0.4011 |
| 0.6621        | 0.9114 | 6400  | 0.5044          | 0.3804 |
| 0.6705        | 0.9399 | 6600  | 0.4999          | 0.3896 |
| 0.6705        | 0.9684 | 6800  | 0.5097          | 0.4053 |
| 0.6665        | 0.9969 | 7000  | 0.4925          | 0.3785 |
| 0.6665        | 1.0253 | 7200  | 0.4896          | 0.3689 |
| 0.6665        | 1.0538 | 7400  | 0.4749          | 0.3687 |
| 0.5826        | 1.0823 | 7600  | 0.4684          | 0.3628 |
| 0.5826        | 1.1108 | 7800  | 0.4729          | 0.3585 |
| 0.5836        | 1.1393 | 8000  | 0.4641          | 0.3553 |
| 0.5836        | 1.1678 | 8200  | 0.4575          | 0.3530 |
| 0.5836        | 1.1962 | 8400  | 0.4585          | 0.3486 |
| 0.5199        | 1.2247 | 8600  | 0.4549          | 0.3451 |
| 0.5199        | 1.2532 | 8800  | 0.4521          | 0.3408 |
| 0.5268        | 1.2817 | 9000  | 0.4425          | 0.3395 |
| 0.5268        | 1.3102 | 9200  | 0.4407          | 0.3362 |
| 0.5268        | 1.3386 | 9400  | 0.4383          | 0.3340 |
| 0.5013        | 1.3671 | 9600  | 0.4357          | 0.3325 |
| 0.5013        | 1.3956 | 9800  | 0.4350          | 0.3317 |
| 0.5095        | 1.4241 | 10000 | 0.4345          | 0.3308 |


### Framework versions

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