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---
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- xtreme_s
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod7
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: xtreme_s
type: xtreme_s
config: fleurs.id_id
split: test
args: fleurs.id_id
metrics:
- type: wer
value: 0.5133213590779824
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_Prod7
This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the xtreme_s dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1411
- Wer: 0.5133
## 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
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 600
- num_epochs: 180
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 4.9813 | 18.18 | 300 | 2.8480 | 1.0 |
| 1.5729 | 36.36 | 600 | 0.8808 | 0.7159 |
| 0.219 | 54.55 | 900 | 0.9209 | 0.5983 |
| 0.1213 | 72.73 | 1200 | 0.9869 | 0.6005 |
| 0.0898 | 90.91 | 1500 | 1.0485 | 0.5840 |
| 0.0668 | 109.09 | 1800 | 1.0746 | 0.5514 |
| 0.0499 | 127.27 | 2100 | 1.0648 | 0.5341 |
| 0.0372 | 145.45 | 2400 | 1.1656 | 0.5280 |
| 0.0292 | 163.64 | 2700 | 1.1411 | 0.5133 |
### Framework versions
- Transformers 4.37.2
- Pytorch 2.2.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1
|