---
library_name: transformers
license: mit
base_model: catsOfpeople/speecht5_finetuned_emirhan_soomea
tags:
- generated_from_trainer
model-index:
- name: speecht5_soome-V2
  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_soome-V2

This model is a fine-tuned version of [catsOfpeople/speecht5_finetuned_emirhan_soomea](https://huggingface.co/catsOfpeople/speecht5_finetuned_emirhan_soomea) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2695

## 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: 16
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 3500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step | Validation Loss |
|:-------------:|:--------:|:----:|:---------------:|
| 0.9648        | 4.5198   | 100  | 0.4308          |
| 0.4495        | 9.0395   | 200  | 0.3583          |
| 0.384         | 13.5593  | 300  | 0.3418          |
| 0.3637        | 18.0791  | 400  | 0.3177          |
| 0.3443        | 22.5989  | 500  | 0.3119          |
| 0.3366        | 27.1186  | 600  | 0.3099          |
| 0.3328        | 31.6384  | 700  | 0.3222          |
| 0.3238        | 36.1582  | 800  | 0.3091          |
| 0.3196        | 40.6780  | 900  | 0.2960          |
| 0.3156        | 45.1977  | 1000 | 0.2977          |
| 0.3123        | 49.7175  | 1100 | 0.2960          |
| 0.3107        | 54.2373  | 1200 | 0.2904          |
| 0.3029        | 58.7571  | 1300 | 0.2891          |
| 0.2978        | 63.2768  | 1400 | 0.2904          |
| 0.3012        | 67.7966  | 1500 | 0.2855          |
| 0.2977        | 72.3164  | 1600 | 0.2863          |
| 0.2915        | 76.8362  | 1700 | 0.2855          |
| 0.2935        | 81.3559  | 1800 | 0.2853          |
| 0.2877        | 85.8757  | 1900 | 0.2794          |
| 0.2839        | 90.3955  | 2000 | 0.2820          |
| 0.2847        | 94.9153  | 2100 | 0.2781          |
| 0.2831        | 99.4350  | 2200 | 0.2799          |
| 0.283         | 103.9548 | 2300 | 0.2811          |
| 0.2792        | 108.4746 | 2400 | 0.2774          |
| 0.2788        | 112.9944 | 2500 | 0.2813          |
| 0.2793        | 117.5141 | 2600 | 0.2755          |
| 0.2746        | 122.0339 | 2700 | 0.2769          |
| 0.2735        | 126.5537 | 2800 | 0.2729          |
| 0.2728        | 131.0734 | 2900 | 0.2764          |
| 0.2735        | 135.5932 | 3000 | 0.2751          |
| 0.2726        | 140.1130 | 3100 | 0.2754          |
| 0.2691        | 144.6328 | 3200 | 0.2707          |
| 0.2711        | 149.1525 | 3300 | 0.2717          |
| 0.2679        | 153.6723 | 3400 | 0.2724          |
| 0.2665        | 158.1921 | 3500 | 0.2695          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1