|
--- |
|
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 |
|
|
