File size: 2,586 Bytes
2a000e6 |
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 |
---
library_name: transformers
license: mit
base_model: maghrane/speecht5_finetuned_marar1000
tags:
- generated_from_trainer
model-index:
- name: speecht5_finetuned_marar2000
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_marar2000
This model is a fine-tuned version of [maghrane/speecht5_finetuned_marar1000](https://huggingface.co/maghrane/speecht5_finetuned_marar1000) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4801
## 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: 1
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 8
- 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: 100
- training_steps: 2000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-------:|:----:|:---------------:|
| 0.528 | 0.7976 | 100 | 0.5440 |
| 0.5453 | 1.5952 | 200 | 0.5655 |
| 0.5395 | 2.3928 | 300 | 0.5418 |
| 0.5421 | 3.1904 | 400 | 0.5570 |
| 0.5384 | 3.9880 | 500 | 0.5324 |
| 0.5447 | 4.7856 | 600 | 0.5454 |
| 0.5343 | 5.5833 | 700 | 0.5220 |
| 0.5165 | 6.3809 | 800 | 0.5269 |
| 0.5171 | 7.1785 | 900 | 0.5223 |
| 0.507 | 7.9761 | 1000 | 0.5227 |
| 0.5021 | 8.7737 | 1100 | 0.5052 |
| 0.4982 | 9.5713 | 1200 | 0.5081 |
| 0.488 | 10.3689 | 1300 | 0.5026 |
| 0.4787 | 11.1665 | 1400 | 0.4902 |
| 0.4849 | 11.9641 | 1500 | 0.4936 |
| 0.4778 | 12.7617 | 1600 | 0.4934 |
| 0.4646 | 13.5593 | 1700 | 0.4858 |
| 0.4615 | 14.3569 | 1800 | 0.4894 |
| 0.4716 | 15.1545 | 1900 | 0.4832 |
| 0.4607 | 15.9521 | 2000 | 0.4801 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.5.1+cu121
- Tokenizers 0.20.3
|