---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
base_model: nandovallec/whisper-tiny-bg-l
model-index:
- name: whisper-tiny-order
  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-tiny-order

This model is a fine-tuned version of [nandovallec/whisper-tiny-bg-l](https://huggingface.co/nandovallec/whisper-tiny-bg-l) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0015
- Wer: 0.0

## 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: 16
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 150
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer      |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 0.5799        | 5.0   | 5    | 1.8414          | 116.3934 |
| 0.2647        | 10.0  | 10   | 0.7719          | 61.4754  |
| 0.1199        | 15.0  | 15   | 0.3593          | 34.4262  |
| 0.063         | 20.0  | 20   | 0.1827          | 18.8525  |
| 0.0257        | 25.0  | 25   | 0.0710          | 4.9180   |
| 0.0103        | 30.0  | 30   | 0.0294          | 0.8197   |
| 0.0045        | 35.0  | 35   | 0.0149          | 0.0      |
| 0.0028        | 40.0  | 40   | 0.0094          | 0.0      |
| 0.0019        | 45.0  | 45   | 0.0064          | 0.0      |
| 0.0014        | 50.0  | 50   | 0.0048          | 0.0      |
| 0.0011        | 55.0  | 55   | 0.0038          | 0.0      |
| 0.0009        | 60.0  | 60   | 0.0032          | 0.0      |
| 0.0008        | 65.0  | 65   | 0.0028          | 0.0      |
| 0.0007        | 70.0  | 70   | 0.0025          | 0.0      |
| 0.0006        | 75.0  | 75   | 0.0023          | 0.0      |
| 0.0006        | 80.0  | 80   | 0.0022          | 0.0      |
| 0.0006        | 85.0  | 85   | 0.0021          | 0.0      |
| 0.0005        | 90.0  | 90   | 0.0020          | 0.0      |
| 0.0005        | 95.0  | 95   | 0.0019          | 0.0      |
| 0.0005        | 100.0 | 100  | 0.0018          | 0.0      |
| 0.0005        | 105.0 | 105  | 0.0017          | 0.0      |
| 0.0005        | 110.0 | 110  | 0.0017          | 0.0      |
| 0.0004        | 115.0 | 115  | 0.0017          | 0.0      |
| 0.0004        | 120.0 | 120  | 0.0016          | 0.0      |
| 0.0004        | 125.0 | 125  | 0.0016          | 0.0      |
| 0.0004        | 130.0 | 130  | 0.0016          | 0.0      |
| 0.0004        | 135.0 | 135  | 0.0016          | 0.0      |
| 0.0004        | 140.0 | 140  | 0.0015          | 0.0      |
| 0.0004        | 145.0 | 145  | 0.0015          | 0.0      |
| 0.0004        | 150.0 | 150  | 0.0015          | 0.0      |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2