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---
license: apache-2.0
tags:
- generated_from_trainer
- automatic-speech-recognition
- NbAiLab/NPSC
- robust-speech-event
- "no"
- nn-NO
- hf-asr-leaderboard
datasets:
- NbAiLab/NPSC
language:
- nn-NO
model-index:
- name: wav2vec2-large-voxrex-npsc-nynorsk
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: NPSC
type: NbAiLab/NPSC
args: 16K_mp3_nynorsk
metrics:
- name: Test (Nynorsk) WER
type: wer
value: 0.12220762155059132
- name: Test (Nynorsk) CER
type: cer
value: 0.04195612578778549
---
<!-- 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. -->
# wav2vec2-large-voxrex-npsc-nynorsk
This model is a fine-tuned version of [KBLab/wav2vec2-large-voxrex](https://huggingface.co/KBLab/wav2vec2-large-voxrex) on the NBAILAB/NPSC - 16K_MP3_NYNORSK dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4142
- Wer: 0.1576
## 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: 7.5e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2000
- num_epochs: 40.0
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 3.086 | 2.17 | 500 | 3.0773 | 1.0 |
| 2.8532 | 4.35 | 1000 | 2.8393 | 1.0 |
| 0.9738 | 6.52 | 1500 | 0.7283 | 0.4890 |
| 0.6763 | 8.7 | 2000 | 0.5340 | 0.3662 |
| 0.5303 | 10.87 | 2500 | 0.4521 | 0.3140 |
| 0.4765 | 13.04 | 3000 | 0.4181 | 0.2853 |
| 0.4219 | 15.22 | 3500 | 0.4156 | 0.2934 |
| 0.3564 | 17.39 | 4000 | 0.3925 | 0.2509 |
| 0.3282 | 19.57 | 4500 | 0.3824 | 0.2420 |
| 0.3118 | 21.74 | 5000 | 0.3636 | 0.2354 |
| 0.2919 | 23.91 | 5500 | 0.3615 | 0.2281 |
| 0.2961 | 26.09 | 6000 | 0.3548 | 0.2255 |
| 0.284 | 28.26 | 6500 | 0.3526 | 0.2209 |
| 0.2566 | 30.43 | 7000 | 0.3526 | 0.2205 |
| 0.2422 | 32.61 | 7500 | 0.3569 | 0.2173 |
| 0.2472 | 34.78 | 8000 | 0.3592 | 0.2166 |
| 0.2337 | 36.96 | 8500 | 0.3625 | 0.2172 |
| 0.2315 | 39.13 | 9000 | 0.3580 | 0.2155 |
### Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.0+cu113
- Datasets 1.18.3
- Tokenizers 0.10.3
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