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---
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
model-index:
- name: zlm_b64_le4_s12000
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. -->
# zlm_b64_le4_s12000
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: 0.3114
## 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: 32
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- 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: 2000
- training_steps: 12000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5487 | 0.4188 | 500 | 0.4746 |
| 0.483 | 0.8375 | 1000 | 0.4227 |
| 0.432 | 1.2563 | 1500 | 0.3983 |
| 0.429 | 1.6750 | 2000 | 0.3953 |
| 0.4168 | 2.0938 | 2500 | 0.3701 |
| 0.4021 | 2.5126 | 3000 | 0.3613 |
| 0.3925 | 2.9313 | 3500 | 0.3509 |
| 0.3839 | 3.3501 | 4000 | 0.3506 |
| 0.3798 | 3.7688 | 4500 | 0.3423 |
| 0.3693 | 4.1876 | 5000 | 0.3375 |
| 0.3712 | 4.6064 | 5500 | 0.3367 |
| 0.3668 | 5.0251 | 6000 | 0.3316 |
| 0.3635 | 5.4439 | 6500 | 0.3291 |
| 0.3543 | 5.8626 | 7000 | 0.3250 |
| 0.3526 | 6.2814 | 7500 | 0.3221 |
| 0.3525 | 6.7002 | 8000 | 0.3218 |
| 0.3513 | 7.1189 | 8500 | 0.3182 |
| 0.346 | 7.5377 | 9000 | 0.3163 |
| 0.3448 | 7.9564 | 9500 | 0.3162 |
| 0.3563 | 8.3752 | 10000 | 0.3145 |
| 0.3449 | 8.7940 | 10500 | 0.3126 |
| 0.3436 | 9.2127 | 11000 | 0.3128 |
| 0.3413 | 9.6315 | 11500 | 0.3121 |
| 0.3397 | 10.0503 | 12000 | 0.3114 |
### Framework versions
- Transformers 4.41.0.dev0
- Pytorch 2.2.1+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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