---
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium.en-cit-do015-wd0-lr1e-06-1000
  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.en-cit-do015-wd0-lr1e-06-1000

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6953
- Wer Ortho: 26.2768
- Wer: 14.7572

## 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-06
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 100
- training_steps: 500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| No log        | 0.4444 | 25   | 1.5811          | 45.2632   | 31.9044 |
| 1.7463        | 0.8889 | 50   | 1.3848          | 39.1033   | 27.0106 |
| 1.7463        | 1.3333 | 75   | 1.2178          | 35.7505   | 23.0273 |
| 1.3387        | 1.7778 | 100  | 1.0166          | 36.1014   | 23.4446 |
| 1.3387        | 2.2222 | 125  | 0.8784          | 31.9298   | 19.1958 |
| 0.988         | 2.6667 | 150  | 0.8340          | 30.8382   | 18.4750 |
| 0.988         | 3.1111 | 175  | 0.8027          | 30.3314   | 17.7162 |
| 0.8856        | 3.5556 | 200  | 0.7812          | 29.6686   | 17.4127 |
| 0.8856        | 4.0    | 225  | 0.7651          | 30.1365   | 17.6783 |
| 0.7927        | 4.4444 | 250  | 0.7515          | 29.2008   | 16.8816 |
| 0.7927        | 4.8889 | 275  | 0.7402          | 28.2651   | 15.6677 |
| 0.7482        | 5.3333 | 300  | 0.7300          | 27.9922   | 15.5159 |
| 0.7482        | 5.7778 | 325  | 0.7217          | 27.8752   | 15.6677 |
| 0.7275        | 6.2222 | 350  | 0.7153          | 27.4854   | 15.4021 |
| 0.7275        | 6.6667 | 375  | 0.7085          | 27.3684   | 15.3642 |
| 0.7003        | 7.1111 | 400  | 0.7041          | 26.6277   | 14.6813 |
| 0.7003        | 7.5556 | 425  | 0.7002          | 26.3158   | 14.7572 |
| 0.6763        | 8.0    | 450  | 0.6973          | 26.2378   | 14.6055 |
| 0.6763        | 8.4444 | 475  | 0.6963          | 26.4327   | 14.7951 |
| 0.6687        | 8.8889 | 500  | 0.6953          | 26.2768   | 14.7572 |


### Framework versions

- Transformers 4.42.3
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1