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---
license: apache-2.0
base_model: NbAiLab/nb-whisper-tiny
tags:
- generated_from_trainer
datasets:
- samromur_asr
metrics:
- wer
model-index:
- name: whisper-tiny-no-is-5k-steps
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: samromur_asr
type: samromur_asr
config: samromur_asr
split: test
args: samromur_asr
metrics:
- name: Wer
type: wer
value: 51.60346372051359
---
<!-- 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/blydklsj)
# whisper-tiny-no-is-5k-steps
This model is a fine-tuned version of [NbAiLab/nb-whisper-tiny](https://huggingface.co/NbAiLab/nb-whisper-tiny) on the samromur_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7830
- Wer: 51.6035
## 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: 5000
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:------:|:----:|:---------------:|:-------:|
| 1.2696 | 0.1778 | 1000 | 1.3551 | 69.4512 |
| 0.9101 | 0.3556 | 2000 | 0.9833 | 60.0096 |
| 0.7626 | 0.5333 | 3000 | 0.8596 | 54.7590 |
| 0.7316 | 0.7111 | 4000 | 0.8014 | 52.3165 |
| 0.7269 | 0.8889 | 5000 | 0.7830 | 51.6035 |
### Framework versions
- Transformers 4.42.3
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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