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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- automatic-speech-recognition
- techiaith/commonvoice_16_1_en_cy
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-ft-ccv-en-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-ccv-en-cy
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the TECHIAITH/COMMONVOICE_16_1_EN_CY - DEFAULT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2754
- Wer: 0.2115
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 800
- training_steps: 9000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 6.0574 | 0.25 | 500 | 2.0297 | 0.9991 |
| 1.224 | 0.5 | 1000 | 0.5368 | 0.4342 |
| 0.434 | 0.75 | 1500 | 0.4861 | 0.3891 |
| 0.3295 | 1.01 | 2000 | 0.4301 | 0.3411 |
| 0.2739 | 1.26 | 2500 | 0.3818 | 0.3053 |
| 0.2619 | 1.51 | 3000 | 0.3894 | 0.3060 |
| 0.2517 | 1.76 | 3500 | 0.3497 | 0.2802 |
| 0.2244 | 2.01 | 4000 | 0.3519 | 0.2792 |
| 0.1854 | 2.26 | 4500 | 0.3376 | 0.2718 |
| 0.1779 | 2.51 | 5000 | 0.3206 | 0.2520 |
| 0.1749 | 2.77 | 5500 | 0.3169 | 0.2535 |
| 0.1636 | 3.02 | 6000 | 0.3122 | 0.2465 |
| 0.137 | 3.27 | 6500 | 0.3054 | 0.2382 |
| 0.1311 | 3.52 | 7000 | 0.2956 | 0.2280 |
| 0.1261 | 3.77 | 7500 | 0.2898 | 0.2236 |
| 0.1187 | 4.02 | 8000 | 0.2847 | 0.2176 |
| 0.1011 | 4.27 | 8500 | 0.2763 | 0.2124 |
| 0.0981 | 4.52 | 9000 | 0.2754 | 0.2115 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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