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---
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: nan
- Wer: 1.0
## 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: 8
- 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: 600
- training_steps: 15000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.6156 | 0.0321 | 500 | 1.5867 | 0.9177 |
| 1.0315 | 0.0641 | 1000 | 1.1748 | 0.7888 |
| 0.834 | 0.0962 | 1500 | 1.0393 | 0.7220 |
| 0.7184 | 0.1283 | 2000 | 0.9616 | 0.6637 |
| 0.6655 | 0.1603 | 2500 | 0.9034 | 0.6331 |
| 0.6193 | 0.1924 | 3000 | 0.8615 | 0.6239 |
| 0.5952 | 0.2244 | 3500 | 0.8161 | 0.5866 |
| 0.5622 | 0.2565 | 4000 | 0.8110 | 0.5851 |
| 0.5341 | 0.2886 | 4500 | 0.7580 | 0.5547 |
| 0.522 | 0.3206 | 5000 | 0.7397 | 0.5412 |
| 0.5123 | 0.3527 | 5500 | 0.7229 | 0.5317 |
| 0.4884 | 0.3848 | 6000 | 0.7235 | 0.5165 |
| 0.4658 | 0.4168 | 6500 | 0.6814 | 0.5117 |
| 0.4471 | 0.4489 | 7000 | 0.6623 | 0.4891 |
| 0.4338 | 0.4810 | 7500 | 0.6450 | 0.4914 |
| 0.4267 | 0.5130 | 8000 | 0.6256 | 0.4685 |
| 0.4283 | 0.5451 | 8500 | 0.6343 | 0.4711 |
| 0.4131 | 0.5771 | 9000 | 0.5989 | 0.4487 |
| 0.4317 | 0.6092 | 9500 | 0.7168 | 0.4920 |
| 0.5904 | 0.6413 | 10000 | nan | 0.7310 |
| 0.0513 | 0.6733 | 10500 | nan | 1.0 |
| 0.0 | 0.7054 | 11000 | nan | 1.0 |
| 0.0 | 0.7375 | 11500 | nan | 1.0 |
| 0.0 | 0.7695 | 12000 | nan | 1.0 |
| 0.0 | 0.8016 | 12500 | nan | 1.0 |
| 0.0 | 0.8337 | 13000 | nan | 1.0 |
| 0.0 | 0.8657 | 13500 | nan | 1.0 |
| 0.0 | 0.8978 | 14000 | nan | 1.0 |
| 0.0 | 0.9298 | 14500 | nan | 1.0 |
| 0.0 | 0.9619 | 15000 | nan | 1.0 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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