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---
license: apache-2.0
base_model: NbAiLab/nb-whisper-large
tags:
- generated_from_trainer
datasets:
- samromur_asr
metrics:
- wer
model-index:
- name: whisper-large-no-is-145h-30k-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: 8.020304568527918
---
<!-- 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/a8dup09b)
# whisper-large-no-is-145h-30k-steps
This model is a fine-tuned version of [NbAiLab/nb-whisper-large](https://huggingface.co/NbAiLab/nb-whisper-large) on the samromur_asr dataset.
It achieves the following results on the evaluation set:
- Loss: 0.1280
- Wer: 8.0203
## 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 |
|:-------------:|:------:|:-----:|:---------------:|:-------:|
| 0.3237 | 0.1778 | 1000 | 0.3331 | 24.9280 |
| 0.2334 | 0.3556 | 2000 | 0.2369 | 19.2033 |
| 0.1932 | 0.5333 | 3000 | 0.2121 | 16.7584 |
| 0.1681 | 0.7111 | 4000 | 0.1874 | 14.9669 |
| 0.1487 | 0.8889 | 5000 | 0.1720 | 13.8274 |
| 0.0911 | 1.0667 | 6000 | 0.1644 | 13.2541 |
| 0.0765 | 1.2444 | 7000 | 0.1577 | 12.3332 |
| 0.0843 | 1.4222 | 8000 | 0.1469 | 11.8722 |
| 0.0797 | 1.6 | 9000 | 0.1437 | 11.3156 |
| 0.0778 | 1.7778 | 10000 | 0.1365 | 10.9298 |
| 0.0789 | 1.9556 | 11000 | 0.1329 | 10.7554 |
| 0.039 | 2.1333 | 12000 | 0.1353 | 10.3625 |
| 0.0394 | 2.3111 | 13000 | 0.1399 | 10.2872 |
| 0.0438 | 2.4889 | 14000 | 0.1357 | 10.0926 |
| 0.0365 | 2.6667 | 15000 | 0.1287 | 9.8632 |
| 0.0406 | 2.8444 | 16000 | 0.1266 | 9.6435 |
| 0.0193 | 3.0222 | 17000 | 0.1284 | 9.3258 |
| 0.0181 | 3.2 | 18000 | 0.1309 | 9.3019 |
| 0.0215 | 3.3778 | 19000 | 0.1317 | 9.1299 |
| 0.0207 | 3.5556 | 20000 | 0.1287 | 8.8767 |
| 0.0185 | 3.7333 | 21000 | 0.1285 | 8.8731 |
| 0.0162 | 3.9111 | 22000 | 0.1272 | 8.6581 |
| 0.007 | 4.0889 | 23000 | 0.1285 | 8.6175 |
| 0.0076 | 4.2667 | 24000 | 0.1296 | 8.3655 |
| 0.0074 | 4.4444 | 25000 | 0.1277 | 8.4037 |
| 0.0076 | 4.6222 | 26000 | 0.1289 | 8.3464 |
| 0.006 | 4.8 | 27000 | 0.1257 | 8.1756 |
| 0.0067 | 4.9778 | 28000 | 0.1252 | 8.0979 |
| 0.0025 | 5.1556 | 29000 | 0.1269 | 8.0322 |
| 0.0032 | 5.3333 | 30000 | 0.1280 | 8.0203 |
### Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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