---
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: 483.1183
- Pcc Accuracy: -0.0911
- Pcc Fluency: -0.0702
- Pcc Total Score: -0.0823
- Pcc Content: -0.0799

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
| 3259.2658     | 1.07  | 500  | 2804.9829       | -0.2619      | -0.2376     | -0.2620         | -0.2464     |
| 1980.8576     | 2.13  | 1000 | 2444.1970       | -0.2591      | -0.2359     | -0.2573         | -0.2394     |
| 1728.8568     | 3.2   | 1500 | 1480.2877       | -0.2539      | -0.2310     | -0.2519         | -0.2337     |
| 490.517       | 4.27  | 2000 | 577.7591        | -0.2334      | -0.2102     | -0.2303         | -0.2141     |
| 761.9771      | 5.34  | 2500 | 503.8331        | -0.1885      | -0.1646     | -0.1829         | -0.1714     |
| 286.5463      | 6.4   | 3000 | 496.2837        | -0.1460      | -0.1234     | -0.1390         | -0.1315     |
| 341.2555      | 7.47  | 3500 | 488.9790        | -0.1150      | -0.0937     | -0.1072         | -0.1026     |
| 544.4691      | 8.54  | 4000 | 484.3144        | -0.0955      | -0.0745     | -0.0870         | -0.0841     |
| 377.6802      | 9.61  | 4500 | 483.1183        | -0.0911      | -0.0702     | -0.0823         | -0.0799     |


### Framework versions

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