transformers pytorch whisper automatic-speech-recognition generated_from_trainer base_model:openai/whisper-medium license:apache-2.0 endpoints_compatible region:us
---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper-medium-train_noise4
  results: []
---

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# whisper-medium-train_noise4

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0105
- Wer: 2.0416

## 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: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 6

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer    |
|:-------------:|:-----:|:-----:|:---------------:|:------:|
| 0.1666        | 1.0   | 2863  | 0.0897          | 6.6866 |
| 0.0337        | 2.0   | 5726  | 0.0348          | 3.5587 |
| 0.0088        | 3.0   | 8589  | 0.0206          | 2.5098 |
| 0.0025        | 4.0   | 11452 | 0.0124          | 2.3038 |
| 0.0008        | 5.0   | 14315 | 0.0110          | 1.9667 |
| 0.0002        | 6.0   | 17178 | 0.0105          | 2.0416 |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3
