---
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: 973.4864
- Pcc Accuracy: 0.7547
- Pcc Fluency: 0.7664
- Pcc Total Score: 0.8143
- Pcc Content: nan

## 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: 5.5e-05
- 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: 0.4
- num_epochs: 15

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
| 2390.3109     | 1.95  | 500  | 2342.6951       | nan          | 0.4815      | nan             | nan         |
| 2164.6891     | 3.9   | 1000 | 2318.7217       | nan          | 0.6461      | nan             | nan         |
| 1078.8019     | 5.85  | 1500 | 1029.2085       | 0.6188       | 0.7014      | 0.6845          | nan         |
| 974.6556      | 7.8   | 2000 | 985.5543        | 0.7117       | 0.7355      | 0.7743          | nan         |
| 1002.623      | 9.75  | 2500 | 989.1628        | 0.7401       | 0.7533      | 0.7995          | nan         |
| 947.5643      | 11.7  | 3000 | 972.3806        | 0.7507       | 0.7628      | 0.8103          | nan         |
| 995.6286      | 13.65 | 3500 | 973.4864        | 0.7547       | 0.7664      | 0.8143          | nan         |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.1