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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- audiofolder
metrics:
- wer
model-index:
- name: xls-r-fleurs_nl-run3
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: audiofolder
type: audiofolder
config: default
split: validation
args: default
metrics:
- name: Wer
type: wer
value: 0.42659804983748645
---
<!-- 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. -->
# xls-r-fleurs_nl-run3
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the audiofolder dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5523
- Wer: 0.4266
## 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: 4
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 7.768 | 0.41 | 100 | 3.9649 | 1.0 |
| 3.2646 | 0.82 | 200 | 2.9551 | 1.0 |
| 2.9217 | 1.23 | 300 | 2.9128 | 1.0 |
| 2.9064 | 1.64 | 400 | 2.9067 | 1.0 |
| 2.6775 | 2.05 | 500 | 1.5774 | 0.9177 |
| 1.1026 | 2.47 | 600 | 0.8813 | 0.7216 |
| 0.6905 | 2.88 | 700 | 0.7287 | 0.6138 |
| 0.4936 | 3.29 | 800 | 0.6156 | 0.5439 |
| 0.3837 | 3.7 | 900 | 0.5608 | 0.4992 |
| 0.3176 | 4.11 | 1000 | 0.5326 | 0.4542 |
| 0.2391 | 4.52 | 1100 | 0.5221 | 0.4466 |
| 0.2426 | 4.93 | 1200 | 0.5127 | 0.4328 |
| 0.1882 | 5.34 | 1300 | 0.5311 | 0.4247 |
| 0.1718 | 5.75 | 1400 | 0.5523 | 0.4266 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.4
- Tokenizers 0.13.3
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