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: 0.2651
- Wer: 9.8186

## 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     |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5952        | 0.13  | 30   | 0.3084          | 14.4155 |
| 0.3011        | 0.25  | 60   | 0.2771          | 17.2921 |
| 0.278         | 0.38  | 90   | 0.2652          | 12.2835 |
| 0.2685        | 0.51  | 120  | 0.2496          | 16.0334 |
| 0.2858        | 0.63  | 150  | 0.2387          | 11.5359 |
| 0.2544        | 0.76  | 180  | 0.2352          | 12.7537 |
| 0.2445        | 0.89  | 210  | 0.2288          | 10.5050 |
| 0.2361        | 1.01  | 240  | 0.2276          | 12.7537 |
| 0.1265        | 1.14  | 270  | 0.2309          | 12.4792 |
| 0.1338        | 1.27  | 300  | 0.2316          | 12.7041 |
| 0.1392        | 1.39  | 330  | 0.2285          | 10.8437 |
| 0.1415        | 1.52  | 360  | 0.2284          | 11.8630 |
| 0.1283        | 1.65  | 390  | 0.2266          | 10.9430 |
| 0.1311        | 1.77  | 420  | 0.2288          | 12.4880 |
| 0.1222        | 1.9   | 450  | 0.2201          | 10.8145 |
| 0.1168        | 2.03  | 480  | 0.2257          | 13.6386 |
| 0.0552        | 2.15  | 510  | 0.2346          | 12.0908 |
| 0.0613        | 2.28  | 540  | 0.2244          | 13.8138 |
| 0.0569        | 2.41  | 570  | 0.2306          | 10.9197 |
| 0.0587        | 2.53  | 600  | 0.2332          | 9.7515  |
| 0.0558        | 2.66  | 630  | 0.2352          | 11.8075 |
| 0.0601        | 2.78  | 660  | 0.2295          | 10.7590 |
| 0.0536        | 2.91  | 690  | 0.2294          | 10.9021 |
| 0.051         | 3.04  | 720  | 0.2353          | 11.0394 |
| 0.0244        | 3.16  | 750  | 0.2439          | 10.4845 |
| 0.0218        | 3.29  | 780  | 0.2483          | 11.0511 |
| 0.0218        | 3.42  | 810  | 0.2434          | 10.5517 |
| 0.0222        | 3.54  | 840  | 0.2510          | 9.8741  |
| 0.0209        | 3.67  | 870  | 0.2436          | 10.8466 |
| 0.0219        | 3.8   | 900  | 0.2476          | 10.4465 |
| 0.0228        | 3.92  | 930  | 0.2433          | 11.1767 |
| 0.0149        | 4.05  | 960  | 0.2499          | 10.1808 |
| 0.0079        | 4.18  | 990  | 0.2625          | 10.4290 |
| 0.0083        | 4.3   | 1020 | 0.2650          | 9.9909  |
| 0.0085        | 4.43  | 1050 | 0.2641          | 10.1194 |
| 0.0085        | 4.56  | 1080 | 0.2637          | 10.5750 |
| 0.0077        | 4.68  | 1110 | 0.2649          | 10.0055 |
| 0.0077        | 4.81  | 1140 | 0.2654          | 9.9734  |
| 0.0085        | 4.94  | 1170 | 0.2651          | 9.8186  |


### Framework versions

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