---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-ro_private_dataset
  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. -->

# whisper-medium-ro_private_dataset

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.9763
- Wer Ortho: 104.4025
- Wer: 102.3457

## 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: 32
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer Ortho | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:--------:|
| 0.0288        | 20.0  | 100  | 3.3078          | 118.7421  | 116.9136 |
| 0.0015        | 40.0  | 200  | 3.6434          | 98.9937   | 97.6543  |
| 0.0017        | 60.0  | 300  | 3.6502          | 100.2516  | 99.1358  |
| 0.0002        | 80.0  | 400  | 3.8591          | 105.6604  | 103.5802 |
| 0.0001        | 100.0 | 500  | 3.9031          | 113.8365  | 111.9753 |
| 0.0001        | 120.0 | 600  | 3.9312          | 114.0881  | 112.0988 |
| 0.0001        | 140.0 | 700  | 3.9508          | 101.6352  | 99.7531  |
| 0.0001        | 160.0 | 800  | 3.9650          | 103.5220  | 101.7284 |
| 0.0001        | 180.0 | 900  | 3.9731          | 104.0252  | 101.9753 |
| 0.0001        | 200.0 | 1000 | 3.9763          | 104.4025  | 102.3457 |


### Framework versions

- Transformers 4.46.3
- Pytorch 2.5.1+cu118
- Datasets 3.1.0
- Tokenizers 0.20.3