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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: id
split: test
args: id
metrics:
- type: wer
value: 0.35167772861356933
name: Wer
---
<!-- 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-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3642
- Wer: 0.3517
## 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: 0.0001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9446 | 1.0 | 278 | 2.9150 | 1.0 |
| 2.8395 | 2.0 | 556 | 2.1459 | 1.0 |
| 0.9822 | 3.0 | 834 | 0.5701 | 0.5534 |
| 0.6623 | 4.0 | 1112 | 0.4610 | 0.4699 |
| 0.5834 | 5.0 | 1390 | 0.4262 | 0.4213 |
| 0.4779 | 6.0 | 1668 | 0.4003 | 0.3908 |
| 0.4511 | 7.0 | 1946 | 0.3802 | 0.3731 |
| 0.4298 | 8.0 | 2224 | 0.3814 | 0.3657 |
| 0.4029 | 9.0 | 2502 | 0.3637 | 0.3575 |
| 0.3807 | 10.0 | 2780 | 0.3642 | 0.3517 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|