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README.md
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---
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license: mit
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---
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license: mit
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datasets:
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- SkyWater21/lv_emotions
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language:
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- lv
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base_model:
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- AiLab-IMCS-UL/lvbert
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---
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Fine-tuned [LVBERT](https://huggingface.co/AiLab-IMCS-UL/lvbert) for multi-label emotion classification task.
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Model was trained on [lv_emotions](https://huggingface.co/datasets/SkyWater21/lv_emotions) dataset. This dataset is Latvian translation of [GoEmotions](https://huggingface.co/datasets/go_emotions) and [Twitter Emotions](https://huggingface.co/datasets/SkyWater21/lv_twitter_emotions) dataset. Google Translate was used to generate the machine translation.
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Original 26 emotions were mapped to 6 base emotions as per Dr. Ekman theory.
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Labels predicted by classifier:
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```yaml
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0: anger
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1: disgust
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2: fear
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3: joy
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4: sadness
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5: surprise
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6: neutral
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```
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Seed used for random number generator is 42:
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```python
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def set_seed(seed=42):
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random.seed(seed)
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np.random.seed(seed)
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torch.manual_seed(seed)
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if torch.cuda.is_available():
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torch.cuda.manual_seed_all(seed)
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```
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Training parameters:
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```yaml
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max_length: null
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batch_size: 32
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shuffle: True
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num_workers: 4
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pin_memory: False
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drop_last: False
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optimizer: adam
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lr: 0.000005
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weight_decay: 0
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problem_type: multi_label_classification
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num_epochs: 3
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```
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Evaluation results on test split of [lv_go_emotions](https://huggingface.co/datasets/SkyWater21/lv_emotions/viewer/combined/lv_go_emotions_test)
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| |Precision|Recall|F1-Score|Support|
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|--------------|---------|------|--------|-------|
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|anger | 0.57| 0.36| 0.44| 726|
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|disgust | 0.42| 0.29| 0.35| 123|
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|fear | 0.59| 0.43| 0.50| 98|
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|joy | 0.78| 0.80| 0.79| 2104|
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|sadness | 0.65| 0.42| 0.51| 379|
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|surprise | 0.62| 0.38| 0.47| 677|
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|neutral | 0.66| 0.58| 0.62| 1787|
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|micro avg | 0.70| 0.59| 0.64| 5894|
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|macro avg | 0.61| 0.46| 0.52| 5894|
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|weighted avg | 0.68| 0.59| 0.63| 5894|
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|samples avg | 0.62| 0.61| 0.61| 5894|
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Evaluation results on test split of [lv_twitter_emotions](https://huggingface.co/datasets/SkyWater21/lv_emotions/viewer/combined/lv_twitter_emotions_test)
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TBD
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