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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_improved_data_w_ljspeech
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_improved_data_w_ljspeech
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: 0.5702
## 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: 1e-05
- train_batch_size: 8
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 3000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 0.9234 | 0.8097 | 250 | 0.7694 |
| 0.7666 | 1.6194 | 500 | 0.6657 |
| 0.6923 | 2.4291 | 750 | 0.6291 |
| 0.6783 | 3.2389 | 1000 | 0.6109 |
| 0.6572 | 4.0486 | 1250 | 0.5961 |
| 0.6631 | 4.8583 | 1500 | 0.5909 |
| 0.6413 | 5.6680 | 1750 | 0.5809 |
| 0.6471 | 6.4777 | 2000 | 0.5798 |
| 0.6336 | 7.2874 | 2250 | 0.5733 |
| 0.6353 | 8.0972 | 2500 | 0.5723 |
| 0.6257 | 8.9069 | 2750 | 0.5700 |
| 0.632 | 9.7166 | 3000 | 0.5702 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.1.2
- Datasets 2.17.0
- Tokenizers 0.19.1
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