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---
license: apache-2.0
base_model: NbAiLab/nb-whisper-large
tags:
- generated_from_trainer
datasets:
- ravnursson_asr
metrics:
- wer
model-index:
- name: whisper-large-no-fo-100h-30k-steps
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: ravnursson_asr
type: ravnursson_asr
config: ravnursson_asr
split: test
args: ravnursson_asr
metrics:
- name: Wer
type: wer
value: 4.066841151600563
---
<!-- 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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/setur/huggingface/runs/apivajor)
# whisper-large-no-fo-100h-30k-steps
This model is a fine-tuned version of [NbAiLab/nb-whisper-large](https://huggingface.co/NbAiLab/nb-whisper-large) on the ravnursson_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0743
- Wer: 4.0668
## 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: 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: 500
- training_steps: 30000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.2496 | 0.2320 | 1000 | 0.2656 | 19.1061 |
| 0.162 | 0.4640 | 2000 | 0.1777 | 13.0914 |
| 0.1308 | 0.6961 | 3000 | 0.1410 | 10.9573 |
| 0.1272 | 0.9281 | 4000 | 0.1217 | 9.6889 |
| 0.0629 | 1.1601 | 5000 | 0.1131 | 8.5263 |
| 0.0636 | 1.3921 | 6000 | 0.1089 | 8.4004 |
| 0.053 | 1.6241 | 7000 | 0.1026 | 7.3384 |
| 0.0528 | 1.8561 | 8000 | 0.0911 | 6.9609 |
| 0.0232 | 2.0882 | 9000 | 0.0963 | 6.9307 |
| 0.0218 | 2.3202 | 10000 | 0.0936 | 6.6841 |
| 0.0241 | 2.5522 | 11000 | 0.0868 | 6.4526 |
| 0.0326 | 2.7842 | 12000 | 0.0866 | 6.5331 |
| 0.0136 | 3.0162 | 13000 | 0.0820 | 5.6020 |
| 0.0098 | 3.2483 | 14000 | 0.0822 | 5.5969 |
| 0.0116 | 3.4803 | 15000 | 0.0806 | 5.4812 |
| 0.0117 | 3.7123 | 16000 | 0.0811 | 5.4963 |
| 0.013 | 3.9443 | 17000 | 0.0792 | 5.3704 |
| 0.0042 | 4.1763 | 18000 | 0.0778 | 4.8722 |
| 0.0078 | 4.4084 | 19000 | 0.0795 | 4.8822 |
| 0.0078 | 4.6404 | 20000 | 0.0785 | 4.7010 |
| 0.0076 | 4.8724 | 21000 | 0.0763 | 4.7061 |
| 0.0042 | 5.1044 | 22000 | 0.0753 | 4.5098 |
| 0.0037 | 5.3364 | 23000 | 0.0765 | 4.5400 |
| 0.0027 | 5.5684 | 24000 | 0.0757 | 4.4041 |
| 0.0037 | 5.8005 | 25000 | 0.0745 | 4.4242 |
| 0.0012 | 6.0325 | 26000 | 0.0742 | 4.3336 |
| 0.0006 | 6.2645 | 27000 | 0.0744 | 4.1675 |
| 0.0009 | 6.4965 | 28000 | 0.0760 | 4.1574 |
| 0.0006 | 6.7285 | 29000 | 0.0743 | 4.1222 |
| 0.0017 | 6.9606 | 30000 | 0.0743 | 4.0668 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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