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---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: w2v-bert-2.0-wol-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. -->
# w2v-bert-2.0-wol-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: 0.1008
- Wer: 0.0792
## 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: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 1.6351 | 0.6857 | 300 | 0.2974 | 0.3040 |
| 0.4591 | 1.3714 | 600 | 0.2215 | 0.2307 |
| 0.3833 | 2.0571 | 900 | 0.1950 | 0.1900 |
| 0.329 | 2.7429 | 1200 | 0.1637 | 0.1614 |
| 0.2797 | 3.4286 | 1500 | 0.1515 | 0.1479 |
| 0.2558 | 4.1143 | 1800 | 0.1435 | 0.1337 |
| 0.2166 | 4.8 | 2100 | 0.1296 | 0.1295 |
| 0.1876 | 5.4857 | 2400 | 0.1178 | 0.1129 |
| 0.1695 | 6.1714 | 2700 | 0.1107 | 0.1005 |
| 0.137 | 6.8571 | 3000 | 0.1064 | 0.0933 |
| 0.1078 | 7.5429 | 3300 | 0.1049 | 0.0929 |
| 0.0904 | 8.2286 | 3600 | 0.1002 | 0.0871 |
| 0.0685 | 8.9143 | 3900 | 0.0973 | 0.0810 |
| 0.049 | 9.6 | 4200 | 0.1008 | 0.0792 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.3.1+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
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