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

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: 0.0224

## 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 |
|:-------------:|:-----:|:----:|:---------------:|
| 0.3209        | 0.19  | 100  | 0.3262          |
| 0.2482        | 0.37  | 200  | 0.3101          |
| 0.2726        | 0.56  | 300  | 0.3030          |
| 0.2288        | 0.74  | 400  | 0.2848          |
| 0.2014        | 0.93  | 500  | 0.2586          |
| 0.1277        | 1.11  | 600  | 0.2098          |
| 0.1054        | 1.3   | 700  | 0.1857          |
| 0.1056        | 1.48  | 800  | 0.1449          |
| 0.0842        | 1.67  | 900  | 0.1069          |
| 0.0692        | 1.85  | 1000 | 0.0874          |
| 0.0314        | 2.04  | 1100 | 0.0628          |
| 0.0265        | 2.22  | 1200 | 0.0515          |
| 0.0154        | 2.41  | 1300 | 0.0443          |
| 0.0127        | 2.59  | 1400 | 0.0382          |
| 0.0237        | 2.78  | 1500 | 0.0290          |
| 0.0119        | 2.96  | 1600 | 0.0224          |


### Framework versions

- Transformers 4.33.0.dev0
- Pytorch 2.0.1+cu118
- Datasets 2.14.4
- Tokenizers 0.13.3