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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- 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 an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5324
- Wer: 0.4014
## 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: 10000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:------:|
| 4.7051 | 0.0321 | 500 | 1.7504 | 0.9570 |
| 1.0409 | 0.0641 | 1000 | 1.1511 | 0.7761 |
| 0.8183 | 0.0962 | 1500 | 1.0506 | 0.7097 |
| 0.7091 | 0.1283 | 2000 | 0.9421 | 0.6610 |
| 0.6547 | 0.1603 | 2500 | 0.8726 | 0.6128 |
| 0.6088 | 0.1924 | 3000 | 0.8246 | 0.5990 |
| 0.5781 | 0.2244 | 3500 | 0.8025 | 0.5747 |
| 0.5429 | 0.2565 | 4000 | 0.7360 | 0.5305 |
| 0.5104 | 0.2886 | 4500 | 0.7335 | 0.5394 |
| 0.501 | 0.3206 | 5000 | 0.6933 | 0.5088 |
| 0.4708 | 0.3527 | 5500 | 0.6770 | 0.5113 |
| 0.4526 | 0.3848 | 6000 | 0.6609 | 0.4806 |
| 0.4235 | 0.4168 | 6500 | 0.6373 | 0.4858 |
| 0.4032 | 0.4489 | 7000 | 0.6048 | 0.4466 |
| 0.3863 | 0.4810 | 7500 | 0.5946 | 0.4432 |
| 0.3766 | 0.5130 | 8000 | 0.5737 | 0.4298 |
| 0.3746 | 0.5451 | 8500 | 0.5668 | 0.4248 |
| 0.3586 | 0.5771 | 9000 | 0.5485 | 0.4101 |
| 0.3552 | 0.6092 | 9500 | 0.5378 | 0.4032 |
| 0.3326 | 0.6413 | 10000 | 0.5324 | 0.4014 |
### Framework versions
- Transformers 4.44.0
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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