whisper-1-dutch / README.md
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---
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: 0.2995
- Wer: 10.8891
## 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 |
|:-------------:|:-----:|:----:|:---------------:|:-------:|
| 0.5753 | 0.13 | 30 | 0.3392 | 14.8670 |
| 0.2975 | 0.25 | 60 | 0.3042 | 19.4403 |
| 0.2893 | 0.38 | 90 | 0.3097 | 38.1677 |
| 0.2771 | 0.51 | 120 | 0.2772 | 13.8256 |
| 0.2656 | 0.63 | 150 | 0.2709 | 15.7969 |
| 0.2518 | 0.76 | 180 | 0.2602 | 14.6440 |
| 0.2419 | 0.89 | 210 | 0.2567 | 16.0404 |
| 0.2391 | 1.01 | 240 | 0.2599 | 13.9781 |
| 0.1319 | 1.14 | 270 | 0.2546 | 13.2594 |
| 0.128 | 1.27 | 300 | 0.2591 | 18.8448 |
| 0.1299 | 1.39 | 330 | 0.2599 | 11.7135 |
| 0.1261 | 1.52 | 360 | 0.2587 | 13.1303 |
| 0.1329 | 1.65 | 390 | 0.2541 | 12.4850 |
| 0.1303 | 1.77 | 420 | 0.2501 | 11.9980 |
| 0.115 | 1.9 | 450 | 0.2506 | 13.2799 |
| 0.1189 | 2.03 | 480 | 0.2486 | 11.0270 |
| 0.0577 | 2.15 | 510 | 0.2554 | 12.2532 |
| 0.0566 | 2.28 | 540 | 0.2587 | 11.3702 |
| 0.0573 | 2.41 | 570 | 0.2651 | 10.9390 |
| 0.0533 | 2.53 | 600 | 0.2590 | 11.1473 |
| 0.0519 | 2.66 | 630 | 0.2636 | 10.8363 |
| 0.056 | 2.78 | 660 | 0.2577 | 11.3732 |
| 0.062 | 2.91 | 690 | 0.2537 | 11.9833 |
| 0.0447 | 3.04 | 720 | 0.2675 | 11.7017 |
| 0.0232 | 3.16 | 750 | 0.2757 | 11.7927 |
| 0.0237 | 3.29 | 780 | 0.2751 | 12.5378 |
| 0.0216 | 3.42 | 810 | 0.2791 | 12.0244 |
| 0.0195 | 3.54 | 840 | 0.2787 | 10.9390 |
| 0.022 | 3.67 | 870 | 0.2749 | 12.4967 |
| 0.0213 | 3.8 | 900 | 0.2757 | 11.9012 |
| 0.0201 | 3.92 | 930 | 0.2735 | 11.5052 |
| 0.0146 | 4.05 | 960 | 0.2854 | 11.3673 |
| 0.0096 | 4.18 | 990 | 0.2956 | 11.7399 |
| 0.008 | 4.3 | 1020 | 0.2955 | 11.8073 |
| 0.008 | 4.43 | 1050 | 0.2963 | 11.8044 |
| 0.0087 | 4.56 | 1080 | 0.2971 | 11.6519 |
| 0.0076 | 4.68 | 1110 | 0.2971 | 11.7017 |
| 0.0073 | 4.81 | 1140 | 0.2982 | 10.8246 |
| 0.0068 | 4.94 | 1170 | 0.2995 | 10.8891 |
### Framework versions
- Transformers 4.38.0.dev0
- Pytorch 2.1.0+cu121
- Datasets 2.14.6
- Tokenizers 0.15.0