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---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- common_voice_13_0
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod11
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: 0.9777378318584071
---
<!-- 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: 1.3207
- Wer: 0.9777
## 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: 0.001
- 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: 5
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| No log | 1.0 | 464 | 2.8781 | 1.0 |
| 3.005 | 2.0 | 928 | 2.5395 | 1.0 |
| 2.7477 | 3.0 | 1392 | 1.6528 | 0.9993 |
| 1.9398 | 4.0 | 1856 | 1.3991 | 0.9854 |
| 1.4528 | 5.0 | 2320 | 1.3207 | 0.9777 |
### Framework versions
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|