metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
datasets:
- xtreme_s
metrics:
- wer
model-index:
- name: wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod9
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: xtreme_s
type: xtreme_s
config: fleurs.id_id
split: test
args: fleurs.id_id
metrics:
- name: Wer
type: wer
value: 0.8831761712318515
wav2vec2-XLS-R-Fleurs-demo-google-colab-Ezra_William_Prod9
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on the xtreme_s dataset. It achieves the following results on the evaluation set:
- Loss: 1.6655
- Wer: 0.8832
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: 0.001
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 50
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|---|---|---|---|---|
| 9.2247 | 1.0 | 39 | 3.1705 | 1.0 |
| 2.9516 | 2.0 | 78 | 2.8732 | 1.0 |
| 2.8953 | 3.0 | 117 | 2.8663 | 1.0 |
| 2.8878 | 4.0 | 156 | 2.8693 | 1.0 |
| 2.8818 | 5.0 | 195 | 2.8656 | 1.0 |
| 2.8814 | 6.0 | 234 | 2.8478 | 1.0 |
| 2.8817 | 7.0 | 273 | 2.8603 | 1.0 |
| 2.8771 | 8.0 | 312 | 2.8647 | 1.0 |
| 2.8811 | 9.0 | 351 | 2.8630 | 1.0 |
| 2.8703 | 10.0 | 390 | 2.8667 | 1.0 |
| 2.8608 | 11.0 | 429 | 2.8429 | 1.0 |
| 2.8578 | 12.0 | 468 | 2.8399 | 1.0 |
| 2.856 | 13.0 | 507 | 2.8531 | 1.0 |
| 2.8438 | 14.0 | 546 | 2.7872 | 1.0 |
| 2.7833 | 15.0 | 585 | 2.7015 | 1.0 |
| 2.7126 | 16.0 | 624 | 2.5606 | 1.0 |
| 2.4797 | 17.0 | 663 | 2.2529 | 1.0 |
| 2.2495 | 18.0 | 702 | 2.1600 | 1.0 |
| 1.8737 | 19.0 | 741 | 1.6194 | 1.0 |
| 1.69 | 20.0 | 780 | 1.4995 | 0.9999 |
| 1.5018 | 21.0 | 819 | 1.3398 | 0.9834 |
| 1.3264 | 22.0 | 858 | 1.2688 | 0.9692 |
| 1.1944 | 23.0 | 897 | 1.2211 | 0.9585 |
| 1.1186 | 24.0 | 936 | 1.1754 | 0.9517 |
| 1.0038 | 25.0 | 975 | 1.2082 | 0.9758 |
| 0.9096 | 26.0 | 1014 | 1.1463 | 0.9210 |
| 0.7954 | 27.0 | 1053 | 1.1530 | 0.9184 |
| 0.7337 | 28.0 | 1092 | 1.1948 | 0.9208 |
| 0.6438 | 29.0 | 1131 | 1.1907 | 0.9021 |
| 0.5933 | 30.0 | 1170 | 1.1994 | 0.9032 |
| 0.5646 | 31.0 | 1209 | 1.2765 | 0.9019 |
| 0.5314 | 32.0 | 1248 | 1.3331 | 0.9387 |
| 0.4208 | 33.0 | 1287 | 1.4003 | 0.9271 |
| 0.3769 | 34.0 | 1326 | 1.4226 | 0.9635 |
| 0.425 | 35.0 | 1365 | 1.3948 | 0.8890 |
| 0.3446 | 36.0 | 1404 | 1.4492 | 0.8901 |
| 0.3411 | 37.0 | 1443 | 1.5271 | 0.9136 |
| 0.3147 | 38.0 | 1482 | 1.4801 | 0.9139 |
| 0.2843 | 39.0 | 1521 | 1.5223 | 0.9011 |
| 0.2908 | 40.0 | 1560 | 1.6087 | 0.8871 |
| 0.2816 | 41.0 | 1599 | 1.5167 | 0.9097 |
| 0.2586 | 42.0 | 1638 | 1.5968 | 0.9129 |
| 0.2428 | 43.0 | 1677 | 1.6335 | 0.9100 |
| 0.2569 | 44.0 | 1716 | 1.5888 | 0.8967 |
| 0.2119 | 45.0 | 1755 | 1.6366 | 0.8910 |
| 0.2496 | 46.0 | 1794 | 1.6392 | 0.8807 |
| 0.2246 | 47.0 | 1833 | 1.6780 | 0.9197 |
| 0.2231 | 48.0 | 1872 | 1.7074 | 0.8969 |
| 0.2083 | 49.0 | 1911 | 1.6566 | 0.8811 |
| 0.2091 | 50.0 | 1950 | 1.6655 | 0.8832 |
Framework versions
- Transformers 4.39.2
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2