metadata
license: apache-2.0
language:
- es
tags:
- generated_from_trainer
- robust-speech-event
- common_voice
datasets:
- common_voice
model-index:
- name: wave2vec-xls-r-300m-es
results:
- task:
name: Speech Recognition
type: automatic-speech-recognition
dataset:
name: Common Voice es
type: common_voice
args: es
metrics:
- name: Test WER
type: wer
value: 14.38
xls-r-300m-es without LM/n-grams
This model is a fine-tuned version of facebook/wav2vec2-xls-r-300m on the common_voice dataset. It achieves the following results on the evaluation set:
- Loss (Test): 0.1900
- Wer (Test): 0.1438
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: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 3.6747 | 0.3 | 400 | 0.6535 | 0.5926 |
| 0.4439 | 0.6 | 800 | 0.3753 | 0.3193 |
| 0.3291 | 0.9 | 1200 | 0.3267 | 0.2721 |
| 0.2644 | 1.2 | 1600 | 0.2816 | 0.2311 |
| 0.24 | 1.5 | 2000 | 0.2647 | 0.2179 |
| 0.2265 | 1.79 | 2400 | 0.2406 | 0.2048 |
| 0.1994 | 2.09 | 2800 | 0.2357 | 0.1869 |
| 0.1613 | 2.39 | 3200 | 0.2242 | 0.1821 |
| 0.1546 | 2.69 | 3600 | 0.2123 | 0.1707 |
| 0.1441 | 2.99 | 4000 | 0.2067 | 0.1619 |
| 0.1138 | 3.29 | 4400 | 0.2044 | 0.1519 |
| 0.1072 | 3.59 | 4800 | 0.1917 | 0.1457 |
| 0.0992 | 3.89 | 5200 | 0.1900 | 0.1438 |
Framework versions
- Transformers 4.16.0.dev0
- Pytorch 1.10.1+cu102
- Datasets 1.17.1.dev0
- Tokenizers 0.11.0