---
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-lr3e-06-FULL
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# whisper-medium.en-cit-do015-wd0-lr3e-06-FULL

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: 0.6528
- Wer Ortho: 32.2429
- Wer: 22.4370

## 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: 3e-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     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 1.8096        | 0.4773 | 50   | 1.2178          | 42.1611   | 31.5966 |
| 1.1953        | 0.9547 | 100  | 0.9199          | 37.1498   | 27.2773 |
| 0.9212        | 1.4320 | 150  | 0.8408          | 34.7486   | 25.2605 |
| 0.8448        | 1.9093 | 200  | 0.7837          | 33.6001   | 24.5210 |
| 0.7174        | 2.3866 | 250  | 0.7344          | 32.5039   | 22.9076 |
| 0.6519        | 2.8640 | 300  | 0.7002          | 33.3391   | 23.4958 |
| 0.5866        | 3.3413 | 350  | 0.6802          | 32.2429   | 22.7395 |
| 0.5625        | 3.8186 | 400  | 0.6631          | 32.6083   | 22.8067 |
| 0.5207        | 4.2959 | 450  | 0.6548          | 32.6779   | 22.8908 |
| 0.5059        | 4.7733 | 500  | 0.6528          | 32.2429   | 22.4370 |


### Framework versions

- Transformers 4.42.4
- Pytorch 1.13.1+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1