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---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec-read_aloud
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. -->
# wav2vec-read_aloud
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: 0.1115
- Pcc Accuracy: 0.7918
- Pcc Fluency: 0.7940
- Pcc Total Score: 0.8472
- Pcc Content: 0.8160
## 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: 0.00055
- train_batch_size: 2
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 12
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.25
- num_epochs: 14
### Training results
| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
| 0.1483 | 1.94 | 500 | 0.1659 | 0.7256 | 0.6982 | 0.7616 | 0.7480 |
| 0.1338 | 3.89 | 1000 | 0.1369 | 0.7706 | 0.7680 | 0.8154 | 0.7835 |
| 0.124 | 5.83 | 1500 | 0.1754 | 0.6686 | 0.6459 | 0.7110 | 0.6823 |
| 0.1147 | 7.77 | 2000 | 0.1149 | 0.7838 | 0.7848 | 0.8368 | 0.8048 |
| 0.1024 | 9.72 | 2500 | 0.1135 | 0.7802 | 0.7819 | 0.8340 | 0.8048 |
| 0.0945 | 11.66 | 3000 | 0.1168 | 0.7891 | 0.7876 | 0.8418 | 0.8095 |
| 0.0945 | 13.61 | 3500 | 0.1115 | 0.7918 | 0.7940 | 0.8472 | 0.8160 |
### Framework versions
- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.1
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