File size: 3,253 Bytes
61eba1f |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 |
---
library_name: transformers
language:
- nl
license: mit
base_model: microsoft/speecht5_tts
tags:
- generated_from_trainer
datasets:
- procit007/saskia_may23_39768
model-index:
- name: speecht5_tts_v1_100
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_tts_v1_100
This model is a fine-tuned version of [microsoft/speecht5_tts](https://huggingface.co/microsoft/speecht5_tts) on the saskia_may23_39768 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4580
## 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: 4
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Use OptimizerNames.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
- num_epochs: 90
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:-----:|:---------------:|
| 0.5267 | 2.7939 | 1000 | 0.4852 |
| 0.4925 | 5.5870 | 2000 | 0.4635 |
| 0.488 | 8.3802 | 3000 | 0.4534 |
| 0.4771 | 11.1733 | 4000 | 0.4528 |
| 0.4703 | 13.9672 | 5000 | 0.4473 |
| 0.4566 | 16.7603 | 6000 | 0.4435 |
| 0.4548 | 19.5535 | 7000 | 0.4532 |
| 0.4499 | 22.3466 | 8000 | 0.4473 |
| 0.456 | 25.1398 | 9000 | 0.4446 |
| 0.4531 | 27.9336 | 10000 | 0.4457 |
| 0.4479 | 30.7268 | 11000 | 0.4495 |
| 0.4461 | 33.5199 | 12000 | 0.4430 |
| 0.4384 | 36.3131 | 13000 | 0.4410 |
| 0.4346 | 39.1062 | 14000 | 0.4475 |
| 0.4399 | 41.9001 | 15000 | 0.4461 |
| 0.4342 | 44.6932 | 16000 | 0.4455 |
| 0.433 | 47.4864 | 17000 | 0.4486 |
| 0.4344 | 50.2795 | 18000 | 0.4568 |
| 0.433 | 53.0727 | 19000 | 0.4490 |
| 0.4318 | 55.8665 | 20000 | 0.4554 |
| 0.4292 | 58.6597 | 21000 | 0.4535 |
| 0.4289 | 61.4528 | 22000 | 0.4510 |
| 0.4284 | 64.2460 | 23000 | 0.4534 |
| 0.43 | 67.0391 | 24000 | 0.4489 |
| 0.4277 | 69.8330 | 25000 | 0.4541 |
| 0.429 | 72.6261 | 26000 | 0.4548 |
| 0.423 | 75.4193 | 27000 | 0.4612 |
| 0.4265 | 78.2124 | 28000 | 0.4516 |
| 0.4344 | 81.0056 | 29000 | 0.4584 |
| 0.4303 | 83.7994 | 30000 | 0.4610 |
| 0.4279 | 86.5926 | 31000 | 0.4562 |
| 0.428 | 89.3857 | 32000 | 0.4580 |
### Framework versions
- Transformers 4.56.0.dev0
- Pytorch 2.6.0+cu124
- Datasets 3.6.0
- Tokenizers 0.21.2
|