---
language:
- en
license: apache-2.0
base_model: openai/whisper-medium.en
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: ./3382
  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. -->

# ./3382

This model is a fine-tuned version of [openai/whisper-medium.en](https://huggingface.co/openai/whisper-medium.en) on the 3382 NYC 1000 dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6304
- Wer Ortho: 32.2501
- Wer: 23.5222

## 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: 200
- training_steps: 1000
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss | Wer Ortho | Wer     |
|:-------------:|:------:|:----:|:---------------:|:---------:|:-------:|
| 1.5524        | 0.5256 | 100  | 1.0430          | 42.1375   | 33.6570 |
| 1.0535        | 1.0512 | 200  | 0.8779          | 37.1493   | 27.9815 |
| 0.8222        | 1.5769 | 300  | 0.7495          | 35.4208   | 26.5674 |
| 0.6909        | 2.1025 | 400  | 0.6826          | 33.2082   | 24.5121 |
| 0.5843        | 2.6281 | 500  | 0.6558          | 32.8625   | 24.1350 |
| 0.5347        | 3.1537 | 600  | 0.6436          | 32.4773   | 23.5693 |
| 0.4819        | 3.6794 | 700  | 0.6377          | 33.5243   | 24.4555 |
| 0.4922        | 4.2050 | 800  | 0.6338          | 31.9933   | 23.0980 |
| 0.4638        | 4.7306 | 900  | 0.6318          | 32.1513   | 23.4845 |
| 0.4362        | 5.2562 | 1000 | 0.6304          | 32.2501   | 23.5222 |


### Framework versions

- Transformers 4.44.0
- Pytorch 1.13.1+cu117
- Datasets 2.21.0
- Tokenizers 0.19.1