---
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: whisper_result
  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_result

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: 0.6586
- Wer Ortho: 52.0665
- Wer: 49.1825

## 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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 2
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 50
- num_epochs: 10
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Wer     | Wer Ortho |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:---------:|
| 0.6179        | 0.03  | 1000  | 0.9762          | 60.3624 | 62.0464   |
| 0.505         | 0.07  | 2000  | 0.8327          | 54.8387 | 57.7117   |
| 0.4921        | 0.1   | 3000  | 0.7555          | 59.6111 | 63.5585   |
| 0.576         | 0.13  | 4000  | 0.7034          | 57.6226 | 58.9214   |
| 0.4169        | 0.17  | 5000  | 0.6763          | 44.5426 | 46.5726   |
| 0.3827        | 0.2   | 6000  | 0.6462          | 44.9403 | 47.0766   |
| 0.3509        | 0.23  | 7000  | 0.6331          | 46.4870 | 48.8407   |
| 0.4012        | 0.26  | 8000  | 0.6170          | 46.8847 | 49.3952   |
| 0.3634        | 0.3   | 9000  | 0.6864          | 47.4294 | 45.3822   |
| 0.3721        | 0.33  | 10000 | 0.6659          | 49.2944 | 46.4870   |
| 0.3198        | 0.36  | 11000 | 0.6586          | 52.0665 | 49.1825   |


### Framework versions

- Transformers 4.28.0
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.13.3