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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: EGPABG
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. -->
# EGPABG
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5020
## 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: 2
- seed: 42
- gradient_accumulation_steps: 8
- 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
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.6281 | 0.2540 | 100 | 0.5862 |
| 0.6048 | 0.5079 | 200 | 0.5734 |
| 0.5792 | 0.7619 | 300 | 0.5444 |
| 0.57 | 1.0159 | 400 | 0.5418 |
| 0.5657 | 1.2698 | 500 | 0.5281 |
| 0.5625 | 1.5238 | 600 | 0.5301 |
| 0.5585 | 1.7778 | 700 | 0.5245 |
| 0.5559 | 2.0317 | 800 | 0.5263 |
| 0.5572 | 2.2857 | 900 | 0.5263 |
| 0.5527 | 2.5397 | 1000 | 0.5161 |
| 0.5524 | 2.7937 | 1100 | 0.5190 |
| 0.544 | 3.0476 | 1200 | 0.5154 |
| 0.542 | 3.3016 | 1300 | 0.5203 |
| 0.5425 | 3.5556 | 1400 | 0.5163 |
| 0.5413 | 3.8095 | 1500 | 0.5099 |
| 0.5328 | 4.0635 | 1600 | 0.5149 |
| 0.5406 | 4.3175 | 1700 | 0.5107 |
| 0.5347 | 4.5714 | 1800 | 0.5079 |
| 0.5362 | 4.8254 | 1900 | 0.5068 |
| 0.5355 | 5.0794 | 2000 | 0.5050 |
| 0.5312 | 5.3333 | 2100 | 0.5061 |
| 0.5282 | 5.5873 | 2200 | 0.5081 |
| 0.5298 | 5.8413 | 2300 | 0.5029 |
| 0.5288 | 6.0952 | 2400 | 0.5028 |
| 0.5371 | 6.3492 | 2500 | 0.5023 |
| 0.525 | 6.6032 | 2600 | 0.5022 |
| 0.5281 | 6.8571 | 2700 | 0.5039 |
| 0.5223 | 7.1111 | 2800 | 0.5023 |
| 0.5231 | 7.3651 | 2900 | 0.5022 |
| 0.5243 | 7.6190 | 3000 | 0.5020 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.0
- Tokenizers 0.19.1
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