---
license: mit
base_model: facebook/w2v-bert-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec-reptiles
  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-reptiles

This model is a fine-tuned version of [facebook/w2v-bert-2.0](https://huggingface.co/facebook/w2v-bert-2.0) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 484.9289
- Pcc Accuracy: -0.1604
- Pcc Fluency: -0.1393
- Pcc Total Score: -0.1591
- Pcc Content: -0.1544

## 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: 4
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.4
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
| 3175.5941     | 1.07  | 500  | 2802.1936       | -0.2863      | -0.2729     | -0.3001         | -0.2745     |
| 1733.457      | 2.13  | 1000 | 2440.8833       | -0.2827      | -0.2779     | -0.2959         | -0.2787     |
| 1890.6879     | 3.2   | 1500 | 1470.4958       | -0.2806      | -0.2763     | -0.2933         | -0.2772     |
| 470.8979      | 4.27  | 2000 | 565.3928        | -0.2658      | -0.2589     | -0.2764         | -0.2621     |
| 881.7893      | 5.34  | 2500 | 501.9731        | -0.2331      | -0.2204     | -0.2394         | -0.2285     |
| 379.352       | 6.4   | 3000 | 497.4395        | -0.2040      | -0.1871     | -0.2068         | -0.1982     |
| 378.5915      | 7.47  | 3500 | 491.6927        | -0.1783      | -0.1590     | -0.1789         | -0.1726     |
| 539.6395      | 8.54  | 4000 | 487.6133        | -0.1639      | -0.1434     | -0.1631         | -0.1582     |
| 319.019       | 9.61  | 4500 | 484.9289        | -0.1604      | -0.1393     | -0.1591         | -0.1544     |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.1
- Tokenizers 0.15.1