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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_binisha
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_finetuned_binisha
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: 0.6198
## 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 |
|:-------------:|:---------:|:----:|:---------------:|
| 0.5825 | 88.8889 | 100 | 0.5775 |
| 0.4984 | 177.7778 | 200 | 0.6064 |
| 0.4252 | 266.6667 | 300 | 0.5800 |
| 0.3997 | 355.5556 | 400 | 0.5745 |
| 0.366 | 444.4444 | 500 | 0.5863 |
| 0.3521 | 533.3333 | 600 | 0.5969 |
| 0.3308 | 622.2222 | 700 | 0.5716 |
| 0.32 | 711.1111 | 800 | 0.5757 |
| 0.3088 | 800.0 | 900 | 0.6095 |
| 0.3006 | 888.8889 | 1000 | 0.6352 |
| 0.2911 | 977.7778 | 1100 | 0.6207 |
| 0.2849 | 1066.6667 | 1200 | 0.6181 |
| 0.2869 | 1155.5556 | 1300 | 0.6321 |
| 0.2853 | 1244.4444 | 1400 | 0.6271 |
| 0.285 | 1333.3333 | 1500 | 0.6198 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.5.0+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
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