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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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod13
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: 0.4416482300884956
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-xlsr-53-CV-demo-google-colab-Ezra_William_Prod13
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: 0.4428
- Wer: 0.4416
## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 9
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9087 | 0.9 | 500 | 2.8298 | 1.0 |
| 2.2394 | 1.8 | 1000 | 1.0606 | 0.8388 |
| 1.1265 | 2.7 | 1500 | 0.6463 | 0.6179 |
| 0.8905 | 3.6 | 2000 | 0.5702 | 0.5400 |
| 0.7668 | 4.5 | 2500 | 0.5134 | 0.4991 |
| 0.7048 | 5.4 | 3000 | 0.4763 | 0.4715 |
| 0.667 | 6.29 | 3500 | 0.4657 | 0.4618 |
| 0.6309 | 7.19 | 4000 | 0.4515 | 0.4506 |
| 0.6002 | 8.09 | 4500 | 0.4407 | 0.4417 |
| 0.6036 | 8.99 | 5000 | 0.4428 | 0.4416 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|