transformers tensorboard safetensors whisper automatic-speech-recognition generated_from_trainer nl base_model:openai/whisper-large-v2 license:apache-2.0 endpoints_compatible region:us
---
language:
- nl
license: apache-2.0
base_model: openai/whisper-large-v2
tags:
- generated_from_trainer
metrics:
- wer
model-index:
- name: Whisper Large V2
  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

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: 0.2572
- Wer: 9.3873

## 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: 3e-05
- train_batch_size: 16
- 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: 20
- num_epochs: 5

### Training results

| Training Loss | Epoch | Step | Validation Loss | Wer     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5724        | 0.49  | 30   | 0.2638          | 10.5041 |
| 0.2659        | 0.98  | 60   | 0.2264          | 9.9205  |
| 0.1374        | 1.48  | 90   | 0.2247          | 9.6992  |
| 0.1421        | 1.97  | 120  | 0.2209          | 10.2626 |
| 0.0576        | 2.46  | 150  | 0.2297          | 9.8098  |
| 0.056         | 2.95  | 180  | 0.2269          | 8.8138  |
| 0.0276        | 3.44  | 210  | 0.2474          | 10.0916 |
| 0.02          | 3.93  | 240  | 0.2427          | 9.4275  |
| 0.0108        | 4.43  | 270  | 0.2527          | 9.4879  |
| 0.0077        | 4.92  | 300  | 0.2572          | 9.3873  |


### Framework versions

- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0
