---
license: apache-2.0
base_model: vitouphy/wav2vec2-xls-r-300m-english
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 [vitouphy/wav2vec2-xls-r-300m-english](https://huggingface.co/vitouphy/wav2vec2-xls-r-300m-english) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2223.3787
- Pcc Accuracy: 0.2187
- Pcc Fluency: 0.0834
- Pcc Total Score: 0.1532
- Pcc Content: 0.2235

## 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: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Pcc Accuracy | Pcc Fluency | Pcc Total Score | Pcc Content |
|:-------------:|:-----:|:----:|:---------------:|:------------:|:-----------:|:---------------:|:-----------:|
| 2728.7846     | 5.0   | 100  | 3196.0576       | 0.3476       | -0.2327     | -0.3110         | 0.2340      |
| 2491.7434     | 10.0  | 200  | 2875.6025       | 0.2791       | -0.0388     | -0.0724         | 0.2475      |
| 1926.2301     | 15.0  | 300  | 2480.8772       | 0.2280       | 0.0499      | 0.1131          | 0.2334      |
| 2065.1381     | 20.0  | 400  | 2265.0391       | 0.2201       | 0.0799      | 0.1478          | 0.2238      |
| 1903.073      | 25.0  | 500  | 2223.3787       | 0.2187       | 0.0834      | 0.1532          | 0.2235      |


### Framework versions

- Transformers 4.37.0
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.15.1