---
library_name: transformers
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
model-index:
- name: whisper-large-v2-medical-9
  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-large-v2-medical-9

This model is a fine-tuned version of [openai/whisper-large-v2](https://huggingface.co/openai/whisper-large-v2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1386

## 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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| No log        | 0.2381 | 20   | 0.5954          |
| 0.9678        | 0.4762 | 40   | 0.3312          |
| 0.372         | 0.7143 | 60   | 0.1767          |
| 0.1657        | 0.9524 | 80   | 0.1568          |
| 0.1297        | 1.1905 | 100  | 0.1507          |
| 0.1297        | 1.4286 | 120  | 0.1455          |
| 0.0923        | 1.6667 | 140  | 0.1403          |
| 0.0974        | 1.9048 | 160  | 0.1376          |
| 0.0753        | 2.1429 | 180  | 0.1389          |
| 0.053         | 2.3810 | 200  | 0.1396          |
| 0.053         | 2.6190 | 220  | 0.1384          |
| 0.0601        | 2.8571 | 240  | 0.1386          |


### Framework versions

- Transformers 4.45.2
- Pytorch 2.4.0+cu121
- Datasets 2.18.0
- Tokenizers 0.20.1