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EGY1.5K
rahafvii/EGY1.5K
EGY1.5K is a machine learning model from rahafvii. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- mit
- Model type
- speecht5
- Access
- Public
- Created
- Oct 23, 2024
- Updated
- Oct 23, 2024
- SHA
- 29e788ba
Base models
Model card
From the Hugging Face model README
<!-- 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. -->
EGY1.5K
This model is a fine-tuned version of microsoft/speecht5_tts on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.4590
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: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3000
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 0.5688 | 1.48 | 100 | 0.5112 |
| 0.5301 | 2.96 | 200 | 0.4908 |
| 0.5023 | 4.44 | 300 | 0.4707 |
| 0.524 | 5.93 | 400 | 0.4797 |
| 0.5001 | 7.41 | 500 | 0.4712 |
| 0.4774 | 8.89 | 600 | 0.4690 |
| 0.4793 | 10.37 | 700 | 0.4627 |
| 0.4666 | 11.85 | 800 | 0.4657 |
| 0.4649 | 13.33 | 900 | 0.4599 |
| 0.4659 | 14.81 | 1000 | 0.4616 |
| 0.4557 | 16.3 | 1100 | 0.4532 |
| 0.4516 | 17.78 | 1200 | 0.4535 |
| 0.4489 | 19.26 | 1300 | 0.4572 |
| 0.4431 | 20.74 | 1400 | 0.4504 |
| 0.4488 | 22.22 | 1500 | 0.4543 |
| 0.4452 | 23.7 | 1600 | 0.4557 |
| 0.4386 | 25.19 | 1700 | 0.4549 |
| 0.4297 | 26.67 | 1800 | 0.4487 |
| 0.4327 | 28.15 | 1900 | 0.4559 |
| 0.425 | 29.63 | 2000 | 0.4572 |
| 0.4251 | 31.11 | 2100 | 0.4531 |
| 0.4295 | 32.59 | 2200 | 0.4500 |
| 0.4258 | 34.07 | 2300 | 0.4561 |
| 0.4222 | 35.56 | 2400 | 0.4550 |
| 0.4119 | 37.04 | 2500 | 0.4569 |
| 0.4208 | 38.52 | 2600 | 0.4573 |
| 0.4145 | 40.0 | 2700 | 0.4568 |
| 0.4215 | 41.48 | 2800 | 0.4585 |
| 0.4141 | 42.96 | 2900 | 0.4594 |
| 0.4136 | 44.44 | 3000 | 0.4590 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.3.0+cu118
- Datasets 3.0.0
- Tokenizers 0.15.2
- Type
- speecht5
- License
- mit
- Created
- Oct 23, 2024
- Updated
- Oct 23, 2024