---
base_model: facebook/wav2vec2-base-960h
datasets:
- FYP/LJ-SpeechLJ
language:
- eng
license: apache-2.0
tags:
- '[finetuned_model, lj_speech11]'
- generated_from_trainer
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: 644.5502

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- 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: 100
- num_epochs: 5
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 653.9298      | 0.3610 | 50   | 646.8141        |
| 840.6591      | 0.7220 | 100  | 646.6405        |
| 1030.5028     | 1.0830 | 150  | 644.3955        |
| 816.1288      | 1.4440 | 200  | 653.6038        |
| 651.3673      | 1.8051 | 250  | 647.9319        |
| 786.9055      | 2.1661 | 300  | 643.6482        |
| 655.5121      | 2.5271 | 350  | 647.9398        |
| 664.6528      | 2.8881 | 400  | 646.9968        |
| 653.3564      | 3.2491 | 450  | 653.9541        |
| 664.1251      | 3.6101 | 500  | 643.4816        |
| 674.7263      | 3.9711 | 550  | 644.8188        |
| 659.9671      | 4.3321 | 600  | 650.9330        |
| 861.3966      | 4.6931 | 650  | 644.5502        |


### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1