---
license: apache-2.0
base_model: facebook/wav2vec2-large-xlsr-53
tags:
- generated_from_trainer
model-index:
- name: wav2vec2_ljspeech_with_stress
  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_ljspeech_with_stress

This model is a fine-tuned version of [facebook/wav2vec2-large-xlsr-53](https://huggingface.co/facebook/wav2vec2-large-xlsr-53) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0431
- Cer: 0.0073

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer    |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 2.9043        | 1.53  | 500  | 3.0446          | 1.0    |
| 1.1195        | 3.05  | 1000 | 0.1302          | 0.0233 |
| 0.1656        | 4.58  | 1500 | 0.0728          | 0.0149 |
| 0.1136        | 6.11  | 2000 | 0.0581          | 0.0122 |
| 0.0852        | 7.63  | 2500 | 0.0508          | 0.0102 |
| 0.0746        | 9.16  | 3000 | 0.0472          | 0.0093 |
| 0.0646        | 10.69 | 3500 | 0.0443          | 0.0084 |
| 0.0588        | 12.21 | 4000 | 0.0442          | 0.0081 |
| 0.0513        | 13.74 | 4500 | 0.0437          | 0.0077 |
| 0.046         | 15.27 | 5000 | 0.0435          | 0.0075 |
| 0.0446        | 16.79 | 5500 | 0.0430          | 0.0075 |
| 0.0429        | 18.32 | 6000 | 0.0433          | 0.0074 |
| 0.0412        | 19.85 | 6500 | 0.0431          | 0.0072 |


### Framework versions

- Transformers 4.34.0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.1