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---
language:
- fr
license: apache-2.0
tags:
- generated_from_trainer
base_model: facebook/wav2vec2-large-xlsr-53
datasets:
- mozilla-foundation/common_voice_17_0
metrics:
- wer
model-index:
- name: acoustic_model2_cv_17_fr_XLSR-53
results:
- task:
type: automatic-speech-recognition
name: Automatic Speech Recognition
dataset:
name: Common Voice 17
type: mozilla-foundation/common_voice_17_0
config: fr
split: test
args: fr
metrics:
- type: wer
value: 0.9923249498169796
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. -->
# acoustic_model2_cv_17_fr_XLSR-53
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 17 dataset.
It achieves the following results on the evaluation set:
- Loss: nan
- Wer: 0.9923
## 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: 0.0003
- 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: 500
- training_steps: 1200
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 16.0974 | 2.105 | 400 | nan | 0.9923 |
| 0.0 | 5.0958 | 800 | nan | 0.9923 |
| 0.0 | 8.0867 | 1200 | nan | 0.9923 |
### Framework versions
- Transformers 4.40.0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
|