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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-xlsr-53-CV-demo-google-colab-Ezra_William_Prod15
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_13_0
type: common_voice_13_0
config: id
split: test
args: id
metrics:
- name: Wer
type: wer
value: 0.29899520648967554
---
<!-- 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-CV-demo-google-colab-Ezra_William_Prod15
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice_13_0 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3344
- Wer: 0.2990
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9553 | 1.0 | 278 | 2.9166 | 1.0 |
| 2.8419 | 2.0 | 556 | 2.1745 | 1.0 |
| 0.9699 | 3.0 | 834 | 0.5752 | 0.5677 |
| 0.6348 | 4.0 | 1112 | 0.4500 | 0.4575 |
| 0.5375 | 5.0 | 1390 | 0.3974 | 0.4070 |
| 0.4354 | 6.0 | 1668 | 0.3678 | 0.3576 |
| 0.3885 | 7.0 | 1946 | 0.3756 | 0.3539 |
| 0.3737 | 8.0 | 2224 | 0.3655 | 0.3345 |
| 0.336 | 9.0 | 2502 | 0.3472 | 0.3215 |
| 0.3014 | 10.0 | 2780 | 0.3395 | 0.3095 |
| 0.3103 | 11.0 | 3058 | 0.3311 | 0.3032 |
| 0.2965 | 12.0 | 3336 | 0.3344 | 0.2990 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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