---
language:
- eng
license: apache-2.0
base_model: facebook/wav2vec2-base-960h
tags:
- '[finetuned_model, lj_speech11]'
- generated_from_trainer
datasets:
- FYP/LJ-SpeechLJ
metrics:
- wer
model-index:
- name: SpeechT5 STT Wav2Vec2
  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. -->

# SpeechT5 STT Wav2Vec2

This model is a fine-tuned version of [facebook/wav2vec2-base-960h](https://huggingface.co/facebook/wav2vec2-base-960h) on the Lj-Speech dataset.
It achieves the following results on the evaluation set:
- Loss: 252.7729
- Wer: 1.0

## 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: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer    |
|:-------------:|:------:|:----:|:---------------:|:------:|
| 130.9264      | 0.5319 | 50   | 256.5228        | 0.9827 |
| 134.1007      | 1.0638 | 100  | 256.2832        | 0.9827 |
| 131.0841      | 1.5957 | 150  | 253.9561        | 0.9827 |
| 132.4283      | 2.1277 | 200  | 254.4677        | 0.9827 |
| 137.3693      | 2.6596 | 250  | 254.6855        | 1.0    |
| 128.1369      | 3.1915 | 300  | 252.8348        | 1.0    |
| 132.3826      | 3.7234 | 350  | 254.7122        | 1.0    |
| 130.9401      | 4.2553 | 400  | 254.6629        | 1.0    |
| 129.5693      | 4.7872 | 450  | 252.7729        | 1.0    |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1