|
--- |
|
license: mit |
|
base_model: Edmon02/speecht5_finetuned_voxpopuli_hy |
|
tags: |
|
- generated_from_trainer |
|
datasets: |
|
- common_voice_17_0 |
|
model-index: |
|
- name: speecht5_finetuned_voxpopuli_hy |
|
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_voxpopuli_hy |
|
|
|
This model is a fine-tuned version of [Edmon02/speecht5_finetuned_voxpopuli_hy](https://huggingface.co/Edmon02/speecht5_finetuned_voxpopuli_hy) on the common_voice_17_0 dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.5088 |
|
|
|
## 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: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- lr_scheduler_warmup_steps: 250 |
|
- training_steps: 4000 |
|
- mixed_precision_training: Native AMP |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|:-------------:|:------:|:----:|:---------------:| |
|
| 0.5974 | 1.2114 | 500 | 0.5489 | |
|
| 0.57 | 2.4228 | 1000 | 0.5261 | |
|
| 0.5684 | 3.6342 | 1500 | 0.5201 | |
|
| 0.5516 | 4.8455 | 2000 | 0.5144 | |
|
| 0.5521 | 6.0569 | 2500 | 0.5134 | |
|
| 0.5436 | 7.2683 | 3000 | 0.5116 | |
|
| 0.5434 | 8.4797 | 3500 | 0.5105 | |
|
| 0.5449 | 9.6911 | 4000 | 0.5088 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.42.4 |
|
- Pytorch 2.3.1+cu121 |
|
- Datasets 2.20.0 |
|
- Tokenizers 0.19.1 |
|
|
