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---
license: apache-2.0
base_model: facebook/wav2vec2-xls-r-300m
tags:
- generated_from_trainer
datasets:
- nb_samtale
metrics:
- wer
model-index:
- name: wav2vec2-classic-300m-norwegian-colab
results:
- task:
name: Automatic Speech Recognition
type: automatic-speech-recognition
dataset:
name: nb_samtale
type: nb_samtale
config: annotations
split: test
args: annotations
metrics:
- name: Wer
type: wer
value: 0.7528477035956058
---
<!-- 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-classic-300m-norwegian-colab
This model is a fine-tuned version of [facebook/wav2vec2-xls-r-300m](https://huggingface.co./facebook/wav2vec2-xls-r-300m) on the nb_samtale dataset.
It achieves the following results on the evaluation set:
- Loss: 2.2190
- Wer: 0.7528
## 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: 0.0003
- train_batch_size: 16
- eval_batch_size: 8
- 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: 500
- num_epochs: 30
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Wer |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 4.8141 | 2.57 | 400 | 3.0571 | 1.0 |
| 3.0777 | 5.14 | 800 | 2.9987 | 1.0 |
| 2.7311 | 7.72 | 1200 | 2.5705 | 0.9829 |
| 2.1302 | 10.29 | 1600 | 1.8399 | 0.9225 |
| 1.6827 | 12.86 | 2000 | 1.6372 | 0.8559 |
| 1.312 | 15.43 | 2400 | 1.8908 | 0.9172 |
| 0.9979 | 18.01 | 2800 | 1.7908 | 0.7890 |
| 0.7456 | 20.58 | 3200 | 1.8110 | 0.7720 |
| 0.592 | 23.15 | 3600 | 2.0024 | 0.7686 |
| 0.4946 | 25.72 | 4000 | 2.1173 | 0.7702 |
| 0.4093 | 28.3 | 4400 | 2.2190 | 0.7528 |
### Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
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