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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: 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
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