---
license: apache-2.0
base_model: openai/whisper-medium
tags:
- generated_from_trainer
model-index:
- name: MAScIR_elderly_whisper-medium-LoRA-for_test
  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. -->

# MAScIR_elderly_whisper-medium-LoRA-for_test

This model is a fine-tuned version of [openai/whisper-medium](https://huggingface.co/openai/whisper-medium) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0403

## 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: 0.001
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 200
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.2935        | 0.19  | 100  | 0.2595          |
| 0.3101        | 0.38  | 200  | 0.2421          |
| 0.2404        | 0.57  | 300  | 0.2664          |
| 0.2303        | 0.76  | 400  | 0.2072          |
| 0.2021        | 0.95  | 500  | 0.1893          |
| 0.1075        | 1.14  | 600  | 0.1650          |
| 0.1222        | 1.33  | 700  | 0.1328          |
| 0.1036        | 1.52  | 800  | 0.1077          |
| 0.0908        | 1.71  | 900  | 0.0835          |
| 0.0701        | 1.9   | 1000 | 0.0727          |
| 0.029         | 2.09  | 1100 | 0.0587          |
| 0.0264        | 2.28  | 1200 | 0.0522          |
| 0.0164        | 2.47  | 1300 | 0.0507          |
| 0.0162        | 2.66  | 1400 | 0.0459          |
| 0.0151        | 2.85  | 1500 | 0.0403          |


### Framework versions

- Transformers 4.35.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.14.0