---
license: apache-2.0
base_model: openai/whisper-base.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: abbenedekwhisper-base.en-finetuning3-D3K
  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. -->

# abbenedekwhisper-base.en-finetuning3-D3K

This model is a fine-tuned version of [openai/whisper-base.en](https://huggingface.co/openai/whisper-base.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.3880
- Cer: 68.1692
- Wer: 115.5629
- Ser: 100.0
- Cer Clean: 3.6171
- Wer Clean: 6.2914
- Ser Clean: 7.0175

## 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: 5e-08
- train_batch_size: 16
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 10
- training_steps: 2000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Cer     | Wer      | Ser   | Cer Clean | Wer Clean | Ser Clean |
|:-------------:|:-----:|:----:|:---------------:|:-------:|:--------:|:-----:|:---------:|:---------:|:---------:|
| 7.3491        | 1.06  | 200  | 6.1358          | 64.7746 | 122.5166 | 100.0 | 3.2832    | 5.6291    | 7.0175    |
| 6.162         | 2.13  | 400  | 5.2935          | 64.2181 | 119.8675 | 100.0 | 3.7284    | 6.6225    | 7.8947    |
| 5.3192        | 3.19  | 600  | 4.7534          | 64.6633 | 119.2053 | 100.0 | 3.5058    | 6.2914    | 7.0175    |
| 4.7266        | 4.26  | 800  | 4.3761          | 65.1085 | 118.2119 | 100.0 | 3.2832    | 5.9603    | 6.1404    |
| 4.2728        | 5.32  | 1000 | 4.0472          | 65.9432 | 117.2185 | 100.0 | 3.2276    | 5.9603    | 6.1404    |
| 3.9248        | 6.38  | 1200 | 3.7904          | 66.7223 | 116.2252 | 100.0 | 3.2276    | 5.9603    | 6.1404    |
| 3.6714        | 7.45  | 1400 | 3.6008          | 67.8909 | 117.2185 | 100.0 | 3.1720    | 5.9603    | 6.1404    |
| 3.499         | 8.51  | 1600 | 3.4790          | 69.0595 | 118.2119 | 100.0 | 3.1720    | 5.9603    | 6.1404    |
| 3.393         | 9.57  | 1800 | 3.4106          | 68.9482 | 117.5497 | 100.0 | 3.1720    | 5.9603    | 6.1404    |
| 3.3491        | 10.64 | 2000 | 3.3880          | 68.1692 | 115.5629 | 100.0 | 3.6171    | 6.2914    | 7.0175    |


### Framework versions

- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.14.5
- Tokenizers 0.15.2