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---
license: apache-2.0
tags:
- generated_from_trainer
datasets:
- common_voice
metrics:
- wer
model-index:
- name: wav2vec2-xls-r-300m-en-ar-fr-es
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice
type: common_voice
config: ar
split: test
args: ar
metrics:
- name: Wer
type: wer
value: 0.48692477711277227
---
<!-- 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-300m-en-ar-fr-es
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co/facebook/wav2vec2-xls-r-300m) on the common_voice dataset.
It achieves the following results on the evaluation set:
- Loss: 0.8565
- Wer: 0.4869
## 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
- num_epochs: 20
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 6.3938 | 0.59 | 400 | 3.3703 | 1.0 |
| 2.353 | 1.18 | 800 | 0.9696 | 0.7809 |
| 0.9859 | 1.77 | 1200 | 0.7031 | 0.6515 |
| 0.7685 | 2.35 | 1600 | 0.6575 | 0.6321 |
| 0.6892 | 2.94 | 2000 | 0.6030 | 0.5927 |
| 0.5866 | 3.53 | 2400 | 0.5552 | 0.5541 |
| 0.5496 | 4.12 | 2800 | 0.5805 | 0.5503 |
| 0.4897 | 4.71 | 3200 | 0.5526 | 0.5335 |
| 0.4671 | 5.3 | 3600 | 0.5622 | 0.5507 |
| 0.4346 | 5.89 | 4000 | 0.5641 | 0.5312 |
| 0.3859 | 6.48 | 4400 | 0.5685 | 0.5071 |
| 0.3728 | 7.06 | 4800 | 0.6106 | 0.5157 |
| 0.3243 | 7.65 | 5200 | 0.6782 | 0.5270 |
| 0.3073 | 8.24 | 5600 | 0.6121 | 0.5232 |
| 0.2748 | 8.83 | 6000 | 0.6318 | 0.5209 |
| 0.25 | 9.42 | 6400 | 0.6334 | 0.4906 |
| 0.2477 | 10.01 | 6800 | 0.6403 | 0.5169 |
| 0.2125 | 10.6 | 7200 | 0.6498 | 0.5080 |
| 0.1997 | 11.18 | 7600 | 0.7029 | 0.5153 |
| 0.1803 | 11.77 | 8000 | 0.6796 | 0.5193 |
| 0.1644 | 12.36 | 8400 | 0.7320 | 0.5080 |
| 0.1609 | 12.95 | 8800 | 0.6705 | 0.5081 |
| 0.1419 | 13.54 | 9200 | 0.7108 | 0.5120 |
| 0.1375 | 14.13 | 9600 | 0.7570 | 0.4909 |
| 0.1265 | 14.72 | 10000 | 0.7681 | 0.5044 |
| 0.1152 | 15.31 | 10400 | 0.8180 | 0.5011 |
| 0.1094 | 15.89 | 10800 | 0.7753 | 0.4947 |
| 0.0998 | 16.48 | 11200 | 0.8077 | 0.4972 |
| 0.1019 | 17.07 | 11600 | 0.8189 | 0.4921 |
| 0.0882 | 17.66 | 12000 | 0.8351 | 0.4922 |
| 0.0855 | 18.25 | 12400 | 0.8688 | 0.4902 |
| 0.0826 | 18.84 | 12800 | 0.8476 | 0.4916 |
| 0.0769 | 19.43 | 13200 | 0.8565 | 0.4869 |
### Framework versions
- Transformers 4.28.0
- Pytorch 2.0.1+cu118
- Datasets 1.18.3
- Tokenizers 0.13.3
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