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---
library_name: transformers
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
datasets:
- common_voice_17_0
metrics:
- wer
model-index:
- name: w2v-bert-cv-grain-lg_cv_only
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: common_voice_17_0
type: common_voice_17_0
config: lg
split: test[:10%]
args: lg
metrics:
- name: Wer
type: wer
value: 0.5799642969652421
---
<!-- 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-cv-grain-lg_cv_only
This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the common_voice_17_0 dataset.
It achieves the following results on the evaluation set:
- Loss: inf
- Wer: 0.5800
- Cer: 0.1379
## 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: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 100
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer | Cer |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| 0.5013 | 1.0 | 2221 | inf | 0.2789 | 0.0724 |
| 0.299 | 2.0 | 4442 | inf | 0.2501 | 0.0648 |
| 0.2554 | 3.0 | 6663 | inf | 0.2435 | 0.0685 |
| 0.2411 | 4.0 | 8884 | inf | 0.2447 | 0.0648 |
| 0.2886 | 5.0 | 11105 | inf | 0.2506 | 0.0654 |
| 0.3923 | 6.0 | 13326 | inf | 0.4237 | 0.1108 |
| 2.1779 | 7.0 | 15547 | inf | 0.5612 | 0.1439 |
| 4.5629 | 8.0 | 17768 | inf | 0.5152 | 0.1379 |
| 2.236 | 9.0 | 19989 | inf | 0.5787 | 0.1384 |
| 2.2033 | 10.0 | 22210 | inf | 0.5742 | 0.1375 |
| 2.2047 | 11.0 | 24431 | inf | 0.5784 | 0.1382 |
| 2.2057 | 12.0 | 26652 | inf | 0.5805 | 0.1390 |
| 2.2076 | 13.0 | 28873 | inf | 0.5800 | 0.1379 |
### Framework versions
- Transformers 4.46.1
- Pytorch 2.1.0+cu118
- Datasets 3.1.0
- Tokenizers 0.20.1
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