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---
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
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