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-10hrs-v1
results: []
w2v-bert-2.0-CV_Fleurs_AMMI_ALFFA-sw-10hrs-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: 0.6790
- Wer: 0.2525
- Cer: 0.0897
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: 8
- eval_batch_size: 4
- 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 |
|---|---|---|---|---|---|
| 2.9209 | 1.0 | 710 | 0.9107 | 0.4690 | 0.1399 |
| 0.6799 | 2.0 | 1420 | 0.6451 | 0.3166 | 0.1020 |
| 0.5118 | 3.0 | 2130 | 0.6325 | 0.2602 | 0.0900 |
| 0.4435 | 4.0 | 2840 | 0.5829 | 0.2610 | 0.0951 |
| 0.3857 | 5.0 | 3550 | 0.5528 | 0.2585 | 0.0952 |
| 0.3363 | 6.0 | 4260 | 0.5604 | 0.2449 | 0.0863 |
| 0.3312 | 7.0 | 4970 | 0.6122 | 0.3529 | 0.1307 |
| 0.3306 | 8.0 | 5680 | 0.5529 | 0.2572 | 0.0931 |
| 0.2915 | 9.0 | 6390 | 0.6499 | 0.2584 | 0.0929 |
| 0.2828 | 10.0 | 7100 | 0.6233 | 0.2678 | 0.0954 |
| 0.2664 | 11.0 | 7810 | 0.6266 | 0.2567 | 0.0904 |
| 0.2473 | 12.0 | 8520 | 0.6285 | 0.2561 | 0.0894 |
| 0.2289 | 13.0 | 9230 | 0.6137 | 0.2531 | 0.0901 |
| 0.2102 | 14.0 | 9940 | 0.6440 | 0.2483 | 0.0891 |
| 0.1976 | 15.0 | 10650 | 0.7161 | 0.2724 | 0.0957 |
| 0.1971 | 16.0 | 11360 | 0.6790 | 0.2525 | 0.0897 |
Framework versions
- Transformers 4.46.0
- Pytorch 2.1.0+cu118
- Datasets 3.0.2
- Tokenizers 0.20.1