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---
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- common_voice_13_0
license: apache-2.0
metrics:
- wer
tags:
- generated_from_trainer
model-index:
- name: XLS-R-demo-google-colab-Ezra_William_Prod_3
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: id
split: validation
args: id
metrics:
- type: wer
value: 0.697900059217419
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. -->
# XLS-R-demo-google-colab-Ezra_William_Prod_3
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: 0.7896
- Wer: 0.6979
## 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: 12
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 5.4479 | 1.0 | 121 | 2.9741 | 1.0 |
| 2.9543 | 2.0 | 242 | 2.9297 | 1.0 |
| 2.9306 | 3.0 | 363 | 2.9112 | 1.0 |
| 2.9216 | 4.0 | 484 | 2.9071 | 1.0 |
| 2.8968 | 5.0 | 605 | 2.8713 | 1.0 |
| 2.8822 | 6.0 | 726 | 2.8446 | 1.0 |
| 2.8421 | 7.0 | 847 | 2.5157 | 1.0 |
| 2.5763 | 8.0 | 968 | 1.5780 | 0.9964 |
| 1.9449 | 9.0 | 1089 | 0.9864 | 0.8132 |
| 1.0398 | 10.0 | 1210 | 0.8565 | 0.7348 |
| 0.9162 | 11.0 | 1331 | 0.7941 | 0.7043 |
| 0.8909 | 12.0 | 1452 | 0.7896 | 0.6979 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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