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---
language:
- pt
license: apache-2.0
tags:
- automatic-speech-recognition
- robust-speech-event
- mozilla-foundation/common_voice_8_0
- generated_from_trainer
datasets:
- common_voice
model-index:
- name: xls-r-300m-pt
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: 21.008
- name: Test CER
type: cer
value: 6.117
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Robust Speech Event - Dev Data
type: speech-recognition-community-v2/dev_data
args: fr
metrics:
- name: Validation WER
type: wer
value: 47.812
- name: Validation CER
type: cer
value: 18.805
---
<!-- 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 - PT dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2290
- Wer: 0.2382
## 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: 0.0002
- train_batch_size: 32
- eval_batch_size: 32
- 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: 15.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 3.0952 | 0.64 | 500 | 3.0982 | 1.0 |
| 1.7975 | 1.29 | 1000 | 0.7887 | 0.5651 |
| 1.4138 | 1.93 | 1500 | 0.5238 | 0.4389 |
| 1.344 | 2.57 | 2000 | 0.4775 | 0.4318 |
| 1.2737 | 3.21 | 2500 | 0.4648 | 0.4075 |
| 1.2554 | 3.86 | 3000 | 0.4069 | 0.3678 |
| 1.1996 | 4.5 | 3500 | 0.3914 | 0.3668 |
| 1.1427 | 5.14 | 4000 | 0.3694 | 0.3572 |
| 1.1372 | 5.78 | 4500 | 0.3568 | 0.3501 |
| 1.0831 | 6.43 | 5000 | 0.3331 | 0.3253 |
| 1.1074 | 7.07 | 5500 | 0.3332 | 0.3352 |
| 1.0536 | 7.71 | 6000 | 0.3131 | 0.3152 |
| 1.0248 | 8.35 | 6500 | 0.3024 | 0.3023 |
| 1.0075 | 9.0 | 7000 | 0.2948 | 0.3028 |
| 0.979 | 9.64 | 7500 | 0.2796 | 0.2853 |
| 0.9594 | 10.28 | 8000 | 0.2719 | 0.2789 |
| 0.9172 | 10.93 | 8500 | 0.2620 | 0.2695 |
| 0.9047 | 11.57 | 9000 | 0.2537 | 0.2596 |
| 0.8777 | 12.21 | 9500 | 0.2438 | 0.2525 |
| 0.8629 | 12.85 | 10000 | 0.2409 | 0.2493 |
| 0.8575 | 13.5 | 10500 | 0.2366 | 0.2440 |
| 0.8361 | 14.14 | 11000 | 0.2317 | 0.2385 |
| 0.8126 | 14.78 | 11500 | 0.2290 | 0.2382 |
### 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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