metadata
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: XLS-R_Jibbali_lang
results: []
XLS-R_Jibbali_lang
This model is a fine-tuned version of facebook/wav2vec2-large-xlsr-53 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1752
- Wer: 0.1926
- Cer: 0.0770
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 | Cer |
|---|---|---|---|---|---|
| 16.5992 | 0.99 | 56 | 15.4050 | 1.0 | 0.9812 |
| 3.79 | 2.0 | 113 | 3.3988 | 1.0 | 0.9812 |
| 3.1872 | 2.99 | 169 | 3.1498 | 1.0 | 0.9812 |
| 3.1705 | 4.0 | 226 | 3.1354 | 1.0 | 0.9812 |
| 3.1147 | 4.99 | 282 | 3.0947 | 1.0 | 0.9812 |
| 3.0616 | 6.0 | 339 | 2.9447 | 1.0 | 0.9460 |
| 2.8239 | 6.99 | 395 | 2.6661 | 1.0 | 0.9106 |
| 1.5494 | 8.0 | 452 | 1.0992 | 0.8684 | 0.3804 |
| 0.5291 | 8.99 | 508 | 0.2822 | 0.3026 | 0.1004 |
| 0.2022 | 10.0 | 565 | 0.2019 | 0.2080 | 0.0665 |
| 0.1721 | 10.99 | 621 | 0.2067 | 0.2032 | 0.0841 |
| 0.1705 | 12.0 | 678 | 0.1968 | 0.1996 | 0.0728 |
| 0.0989 | 12.99 | 734 | 0.2038 | 0.1955 | 0.0821 |
| 0.1299 | 14.0 | 791 | 0.1814 | 0.1963 | 0.0837 |
| 0.1352 | 14.99 | 847 | 0.1896 | 0.1941 | 0.0768 |
| 0.0487 | 16.0 | 904 | 0.1951 | 0.1933 | 0.0749 |
| 0.1412 | 16.99 | 960 | 0.1650 | 0.1970 | 0.0818 |
| 0.1027 | 18.0 | 1017 | 0.1720 | 0.1941 | 0.0783 |
| 0.0791 | 18.99 | 1073 | 0.1730 | 0.1933 | 0.0767 |
| 0.0406 | 19.82 | 1120 | 0.1752 | 0.1926 | 0.0770 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.2