ESP_TWICE_DATA / README.md
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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: ESP_TWICE_DATA
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. -->
# ESP_TWICE_DATA
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4606
## 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: 1500
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.5685 | 5.1613 | 100 | 0.5270 |
| 0.5244 | 10.3226 | 200 | 0.4922 |
| 0.5034 | 15.4839 | 300 | 0.4847 |
| 0.4875 | 20.6452 | 400 | 0.4703 |
| 0.4759 | 25.8065 | 500 | 0.4669 |
| 0.4718 | 30.9677 | 600 | 0.4664 |
| 0.4604 | 36.1290 | 700 | 0.4609 |
| 0.4526 | 41.2903 | 800 | 0.4637 |
| 0.4525 | 46.4516 | 900 | 0.4602 |
| 0.4452 | 51.6129 | 1000 | 0.4608 |
| 0.448 | 56.7742 | 1100 | 0.4622 |
| 0.4373 | 61.9355 | 1200 | 0.4580 |
| 0.4326 | 67.0968 | 1300 | 0.4580 |
| 0.4335 | 72.2581 | 1400 | 0.4594 |
| 0.4328 | 77.4194 | 1500 | 0.4606 |
### Framework versions
- Transformers 4.46.0.dev0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.20.0