---
license: apache-2.0
tags:
- automatic-speech-recognition
- w11wo/ljspeech_phonemes
- generated_from_trainer
metrics:
- wer
model-index:
- name: wav2vec2-ljspeech-gruut
  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-gruut

This model is a fine-tuned version of [facebook/wav2vec2-base](https://huggingface.co/facebook/wav2vec2-base) on the W11WO/LJSPEECH_PHONEMES - NA dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0683
- Wer: 0.0099
- Cer: 0.0058

## 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: 30.0
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    | Cer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|:------:|
| No log        | 1.0   | 348   | 2.2818          | 1.0    | 1.0    |
| 2.6692        | 2.0   | 696   | 0.2045          | 0.0527 | 0.0299 |
| 0.2225        | 3.0   | 1044  | 0.1162          | 0.0319 | 0.0189 |
| 0.2225        | 4.0   | 1392  | 0.0927          | 0.0235 | 0.0147 |
| 0.0868        | 5.0   | 1740  | 0.0797          | 0.0218 | 0.0143 |
| 0.0598        | 6.0   | 2088  | 0.0715          | 0.0197 | 0.0128 |
| 0.0598        | 7.0   | 2436  | 0.0652          | 0.0160 | 0.0103 |
| 0.0447        | 8.0   | 2784  | 0.0571          | 0.0152 | 0.0095 |
| 0.0368        | 9.0   | 3132  | 0.0608          | 0.0163 | 0.0112 |
| 0.0368        | 10.0  | 3480  | 0.0586          | 0.0137 | 0.0083 |
| 0.0303        | 11.0  | 3828  | 0.0641          | 0.0141 | 0.0085 |
| 0.0273        | 12.0  | 4176  | 0.0656          | 0.0131 | 0.0079 |
| 0.0232        | 13.0  | 4524  | 0.0690          | 0.0133 | 0.0082 |
| 0.0232        | 14.0  | 4872  | 0.0598          | 0.0128 | 0.0079 |
| 0.0189        | 15.0  | 5220  | 0.0671          | 0.0121 | 0.0074 |
| 0.017         | 16.0  | 5568  | 0.0654          | 0.0114 | 0.0069 |
| 0.017         | 17.0  | 5916  | 0.0751          | 0.0118 | 0.0073 |
| 0.0146        | 18.0  | 6264  | 0.0653          | 0.0112 | 0.0068 |
| 0.0127        | 19.0  | 6612  | 0.0682          | 0.0112 | 0.0069 |
| 0.0127        | 20.0  | 6960  | 0.0678          | 0.0114 | 0.0068 |
| 0.0114        | 21.0  | 7308  | 0.0656          | 0.0111 | 0.0066 |
| 0.0101        | 22.0  | 7656  | 0.0669          | 0.0109 | 0.0066 |
| 0.0092        | 23.0  | 8004  | 0.0677          | 0.0108 | 0.0065 |
| 0.0092        | 24.0  | 8352  | 0.0653          | 0.0104 | 0.0063 |
| 0.0088        | 25.0  | 8700  | 0.0673          | 0.0102 | 0.0063 |
| 0.0074        | 26.0  | 9048  | 0.0669          | 0.0105 | 0.0064 |
| 0.0074        | 27.0  | 9396  | 0.0707          | 0.0101 | 0.0061 |
| 0.0066        | 28.0  | 9744  | 0.0673          | 0.0100 | 0.0060 |
| 0.0058        | 29.0  | 10092 | 0.0689          | 0.0100 | 0.0059 |
| 0.0058        | 30.0  | 10440 | 0.0683          | 0.0099 | 0.0058 |


### Framework versions

- Transformers 4.26.0.dev0
- Pytorch 1.10.0
- Datasets 2.7.1
- Tokenizers 0.13.2