---
license: apache-2.0
tags:
- generated_from_trainer
model-index:
- name: wav2vec2-large-TIMIT-IPA
  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. -->

# wav2vec2-large-TIMIT-IPA

This model is a fine-tuned version of [facebook/wav2vec2-large](https://huggingface.co/facebook/wav2vec2-large) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3130
- Per: 0.0550

## 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: 0.0001
- train_batch_size: 64
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Per    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.3003        | 6.85  | 500  | 3.8093          | 0.9424 |
| 1.7151        | 13.7  | 1000 | 0.2929          | 0.0708 |
| 0.2212        | 20.55 | 1500 | 0.2259          | 0.0575 |
| 0.1241        | 27.4  | 2000 | 0.2716          | 0.0595 |
| 0.0917        | 34.25 | 2500 | 0.2902          | 0.0606 |
| 0.0659        | 41.1  | 3000 | 0.2982          | 0.0570 |
| 0.0532        | 47.95 | 3500 | 0.2770          | 0.0595 |
| 0.0438        | 54.79 | 4000 | 0.2953          | 0.0579 |
| 0.0368        | 61.64 | 4500 | 0.3151          | 0.0572 |
| 0.0303        | 68.49 | 5000 | 0.3425          | 0.0576 |
| 0.0281        | 75.34 | 5500 | 0.3065          | 0.0558 |
| 0.0215        | 82.19 | 6000 | 0.3288          | 0.0558 |
| 0.0185        | 89.04 | 6500 | 0.3288          | 0.0558 |
| 0.018         | 95.89 | 7000 | 0.3130          | 0.0550 |


### Framework versions

- Transformers 4.20.0
- Pytorch 1.12.1+cu113
- Datasets 2.6.2.dev0
- Tokenizers 0.12.1