|
--- |
|
library_name: transformers |
|
license: mit |
|
base_model: facebook/w2v-bert-2.0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- wer |
|
model-index: |
|
- name: W2V2_Bert_BIG-C_BEMBA_5hr_v1 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# W2V2_Bert_BIG-C_BEMBA_5hr_v1 |
|
|
|
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: inf |
|
- Wer: 0.4852 |
|
- Cer: 0.1215 |
|
|
|
## 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: 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: cosine |
|
- lr_scheduler_warmup_ratio: 0.01 |
|
- num_epochs: 100 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:| |
|
| 2.7125 | 1.0 | 80 | inf | 0.8011 | 0.2453 | |
|
| 0.9662 | 2.0 | 160 | inf | 0.6760 | 0.1957 | |
|
| 0.8283 | 3.0 | 240 | inf | 0.5605 | 0.1560 | |
|
| 0.747 | 4.0 | 320 | inf | 0.6229 | 0.2060 | |
|
| 0.6936 | 5.0 | 400 | inf | 0.6425 | 0.1831 | |
|
| 0.6788 | 6.0 | 480 | inf | 0.5411 | 0.1585 | |
|
| 0.6271 | 7.0 | 560 | inf | 0.5229 | 0.1509 | |
|
| 0.7234 | 8.0 | 640 | inf | 0.6888 | 0.2353 | |
|
| 1.1405 | 9.0 | 720 | inf | 0.9791 | 0.5775 | |
|
| 2.4003 | 10.0 | 800 | inf | 0.9988 | 0.9226 | |
|
| 2.6328 | 11.0 | 880 | inf | 0.9986 | 0.9117 | |
|
| 2.9233 | 12.0 | 960 | inf | 1.0 | 0.9986 | |
|
| 3.6687 | 13.0 | 1040 | inf | 1.0 | 0.9970 | |
|
| 3.6827 | 14.0 | 1120 | inf | 1.0 | 0.9970 | |
|
| 3.6799 | 15.0 | 1200 | inf | 1.0 | 0.9970 | |
|
| 3.65 | 16.0 | 1280 | inf | 1.0 | 0.9970 | |
|
| 3.6764 | 17.0 | 1360 | inf | 1.0 | 0.9970 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.44.2 |
|
- Pytorch 2.2.0+cu121 |
|
- Datasets 2.21.0 |
|
- Tokenizers 0.19.1 |
|
|
