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---
language:
- fr
license: apache-2.0
tags:
- automatic-speech-recognition
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
- robust-speech-event
datasets:
- common_voice
model-index:
- name: xls-r-300m-fr
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice 8.0 fr
type: mozilla-foundation/common_voice_8_0
args: fr
metrics:
- name: Test WER
type: wer
value: 36.81
---
<!-- 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. -->
#
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the MOZILLA-FOUNDATION/COMMON_VOICE_8_0 - FR dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2388
- Wer: 0.3681
## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1500
- num_epochs: 2.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 4.3748 | 0.07 | 500 | 3.8784 | 1.0 |
| 2.8068 | 0.14 | 1000 | 2.8289 | 0.9826 |
| 1.6698 | 0.22 | 1500 | 0.8811 | 0.7127 |
| 1.3488 | 0.29 | 2000 | 0.5166 | 0.5369 |
| 1.2239 | 0.36 | 2500 | 0.4105 | 0.4741 |
| 1.1537 | 0.43 | 3000 | 0.3585 | 0.4448 |
| 1.1184 | 0.51 | 3500 | 0.3336 | 0.4292 |
| 1.0968 | 0.58 | 4000 | 0.3195 | 0.4180 |
| 1.0737 | 0.65 | 4500 | 0.3075 | 0.4141 |
| 1.0677 | 0.72 | 5000 | 0.3015 | 0.4089 |
| 1.0462 | 0.8 | 5500 | 0.2971 | 0.4077 |
| 1.0392 | 0.87 | 6000 | 0.2870 | 0.3997 |
| 1.0178 | 0.94 | 6500 | 0.2805 | 0.3963 |
| 0.992 | 1.01 | 7000 | 0.2748 | 0.3935 |
| 1.0197 | 1.09 | 7500 | 0.2691 | 0.3884 |
| 1.0056 | 1.16 | 8000 | 0.2682 | 0.3889 |
| 0.9826 | 1.23 | 8500 | 0.2647 | 0.3868 |
| 0.9815 | 1.3 | 9000 | 0.2603 | 0.3832 |
| 0.9717 | 1.37 | 9500 | 0.2561 | 0.3807 |
| 0.9605 | 1.45 | 10000 | 0.2523 | 0.3783 |
| 0.96 | 1.52 | 10500 | 0.2494 | 0.3788 |
| 0.9442 | 1.59 | 11000 | 0.2478 | 0.3760 |
| 0.9564 | 1.66 | 11500 | 0.2454 | 0.3733 |
| 0.9436 | 1.74 | 12000 | 0.2439 | 0.3747 |
| 0.938 | 1.81 | 12500 | 0.2411 | 0.3716 |
| 0.9353 | 1.88 | 13000 | 0.2397 | 0.3698 |
| 0.9271 | 1.95 | 13500 | 0.2388 | 0.3681 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.2+cu102
- Datasets 1.18.2.dev0
- Tokenizers 0.11.0
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