---
library_name: peft
language:
- sw
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
datasets:
- fsicoli/common_voice_19_0
model-index:
- name: eolang/sw-peft-2
  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. -->

# eolang/sw-peft-2

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the Common Voice 19 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3697

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- 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: 50
- num_epochs: 1
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 1.5084        | 0.0191 | 100  | 1.0225          |
| 0.9199        | 0.0382 | 200  | 0.9041          |
| 0.8295        | 0.0573 | 300  | 0.8428          |
| 0.8404        | 0.0764 | 400  | 0.8142          |
| 0.8215        | 0.0955 | 500  | 0.8141          |
| 0.7527        | 0.1147 | 600  | 0.7640          |
| 0.7494        | 0.1338 | 700  | 0.7652          |
| 0.7693        | 0.1529 | 800  | 0.7081          |
| 0.7104        | 0.1720 | 900  | 0.7238          |
| 0.6975        | 0.1911 | 1000 | 0.6990          |
| 0.7164        | 0.2102 | 1100 | 0.7002          |
| 0.6693        | 0.2293 | 1200 | 0.6842          |
| 0.7043        | 0.2484 | 1300 | 0.6831          |
| 0.6521        | 0.2675 | 1400 | 0.6527          |
| 0.6468        | 0.2866 | 1500 | 0.6563          |
| 0.6376        | 0.3058 | 1600 | 0.6180          |
| 0.6008        | 0.3249 | 1700 | 0.6223          |
| 0.6353        | 0.3440 | 1800 | 0.6113          |
| 0.5885        | 0.3631 | 1900 | 0.6033          |
| 0.598         | 0.3822 | 2000 | 0.5987          |
| 0.5749        | 0.4013 | 2100 | 0.5792          |
| 0.5714        | 0.4204 | 2200 | 0.5772          |
| 0.5438        | 0.4395 | 2300 | 0.5688          |
| 0.5442        | 0.4586 | 2400 | 0.5711          |
| 0.5165        | 0.4777 | 2500 | 0.5588          |
| 0.4971        | 0.4968 | 2600 | 0.5408          |
| 0.5026        | 0.5160 | 2700 | 0.5365          |
| 0.5278        | 0.5351 | 2800 | 0.5112          |
| 0.5371        | 0.5542 | 2900 | 0.5160          |
| 0.5013        | 0.5733 | 3000 | 0.5041          |
| 0.4867        | 0.5924 | 3100 | 0.4978          |
| 0.4938        | 0.6115 | 3200 | 0.4830          |
| 0.4522        | 0.6306 | 3300 | 0.4798          |
| 0.4515        | 0.6497 | 3400 | 0.4751          |
| 0.4593        | 0.6688 | 3500 | 0.4631          |
| 0.4539        | 0.6879 | 3600 | 0.4561          |
| 0.4557        | 0.7071 | 3700 | 0.4467          |
| 0.417         | 0.7262 | 3800 | 0.4419          |
| 0.4251        | 0.7453 | 3900 | 0.4368          |
| 0.4062        | 0.7644 | 4000 | 0.4277          |
| 0.3815        | 0.7835 | 4100 | 0.4271          |
| 0.3832        | 0.8026 | 4200 | 0.4155          |
| 0.3818        | 0.8217 | 4300 | 0.4098          |
| 0.3988        | 0.8408 | 4400 | 0.4005          |
| 0.4073        | 0.8599 | 4500 | 0.3964          |
| 0.3894        | 0.8790 | 4600 | 0.3898          |
| 0.3464        | 0.8981 | 4700 | 0.3858          |
| 0.3626        | 0.9173 | 4800 | 0.3800          |
| 0.3753        | 0.9364 | 4900 | 0.3771          |
| 0.3734        | 0.9555 | 5000 | 0.3733          |
| 0.3362        | 0.9746 | 5100 | 0.3718          |
| 0.3607        | 0.9937 | 5200 | 0.3697          |


### Framework versions

- PEFT 0.14.0
- Transformers 4.47.0
- Pytorch 2.5.1+cu121
- Datasets 3.3.1
- Tokenizers 0.21.0