chichewa_tts_v2 / README.md
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---
library_name: transformers
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- Chithekitale/testing_one
model-index:
- name: Chichewa TTS 1.2
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. -->
# Chichewa TTS 1.2
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the testing_one dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4179
## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- training_steps: 4000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.4355 | 35.7143 | 1000 | 0.4139 |
| 0.4067 | 71.4286 | 2000 | 0.4126 |
| 0.4103 | 107.1429 | 3000 | 0.4144 |
| 0.3979 | 142.8571 | 4000 | 0.4179 |
### Framework versions
- Transformers 4.49.0
- Pytorch 2.7.0.dev20250301+cu118
- Datasets 3.3.2
- Tokenizers 0.21.0