metadata
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-CV_Fleurs_AMMI_ALFFA-sw-20hrs-v1
results: []
w2v-bert-2.0-CV_Fleurs_AMMI_ALFFA-sw-20hrs-v1
This model is a fine-tuned version of facebook/w2v-bert-2.0 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.5645
- Wer: 0.2500
- Cer: 0.0899
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: 5e-05
- train_batch_size: 4
- eval_batch_size: 2
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 100
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|---|---|---|---|---|---|
| 1.7972 | 1.0 | 2970 | 0.6806 | 0.2849 | 0.0958 |
| 0.4586 | 2.0 | 5940 | 0.6101 | 0.2595 | 0.0922 |
| 0.3832 | 3.0 | 8910 | 0.5412 | 0.2290 | 0.0789 |
| 0.3513 | 4.0 | 11880 | 0.4830 | 0.2379 | 0.0865 |
| 0.3284 | 5.0 | 14850 | 0.5698 | 0.2259 | 0.0800 |
| 0.3268 | 6.0 | 17820 | 0.6145 | 0.2308 | 0.0810 |
| 0.3129 | 7.0 | 20790 | 0.5390 | 0.2517 | 0.0883 |
| 0.2935 | 8.0 | 23760 | 0.6146 | 0.2366 | 0.0858 |
| 0.2829 | 9.0 | 26730 | 0.6222 | 0.2571 | 0.0892 |
| 0.2835 | 10.0 | 29700 | 0.6284 | 0.2480 | 0.0907 |
| 0.2709 | 11.0 | 32670 | 0.6553 | 0.2542 | 0.0923 |
| 0.2468 | 12.0 | 35640 | 0.6046 | 0.2406 | 0.0868 |
| 0.2337 | 13.0 | 38610 | 0.6232 | 0.2411 | 0.0880 |
| 0.2037 | 14.0 | 41580 | 0.6318 | 0.2290 | 0.0837 |
| 0.2021 | 15.0 | 44550 | 0.5645 | 0.2500 | 0.0899 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1