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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: 0.4290
- Wer: 0.3378
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 2600
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| No log | 0.0774 | 100 | 3.5325 | 1.0 |
| No log | 0.1549 | 200 | 2.9652 | 1.0 |
| No log | 0.2323 | 300 | 2.8521 | 1.0 |
| No log | 0.3097 | 400 | 1.2473 | 0.8265 |
| 3.7403 | 0.3871 | 500 | 0.9730 | 0.7234 |
| 3.7403 | 0.4646 | 600 | 0.8328 | 0.6178 |
| 3.7403 | 0.5420 | 700 | 0.7426 | 0.5505 |
| 3.7403 | 0.6194 | 800 | 0.7127 | 0.5540 |
| 3.7403 | 0.6969 | 900 | 0.6692 | 0.5080 |
| 0.7271 | 0.7743 | 1000 | 0.6376 | 0.5256 |
| 0.7271 | 0.8517 | 1100 | 0.6119 | 0.4706 |
| 0.7271 | 0.9292 | 1200 | 0.5987 | 0.4651 |
| 0.7271 | 1.0066 | 1300 | 0.5614 | 0.4267 |
| 0.7271 | 1.0840 | 1400 | 0.5463 | 0.4229 |
| 0.5511 | 1.1614 | 1500 | 0.5232 | 0.4079 |
| 0.5511 | 1.2389 | 1600 | 0.5185 | 0.4029 |
| 0.5511 | 1.3163 | 1700 | 0.5090 | 0.4042 |
| 0.5511 | 1.3937 | 1800 | 0.4785 | 0.3851 |
| 0.5511 | 1.4712 | 1900 | 0.4775 | 0.3803 |
| 0.4529 | 1.5486 | 2000 | 0.4677 | 0.3722 |
| 0.4529 | 1.6260 | 2100 | 0.4574 | 0.3544 |
| 0.4529 | 1.7034 | 2200 | 0.4473 | 0.3562 |
| 0.4529 | 1.7809 | 2300 | 0.4437 | 0.3470 |
| 0.4529 | 1.8583 | 2400 | 0.4353 | 0.3450 |
| 0.4149 | 1.9357 | 2500 | 0.4300 | 0.3401 |
| 0.4149 | 2.0132 | 2600 | 0.4290 | 0.3378 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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