--- license: cc-by-sa-4.0 tags: - generated_from_trainer metrics: - accuracy model-index: - name: SloBertAA_Top5_WithOOC results: [] datasets: - gregorgabrovsek/RTVCommentsTop5UsersWithOOC language: - sl --- # SloBertAA_Top5_WithOOC This model is a fine-tuned version of [EMBEDDIA/sloberta](https://huggingface.co/EMBEDDIA/sloberta) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 0.5616 - Accuracy: 0.8946 ## Other related models Models fine-tuned on the RTV datasets: | Base model | Includes the OOC class? | 5 classes | 10 classes | 20 classes | 50 classes | 100 classes | | ------------------- | ----------------------- |:---------:|:----------:|:----------:|:----------:|:-----------:| | SloBERTa | Yes | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top5_WithOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top10_WithOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top20_WithOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top50_WithOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top100_WithOOC) | | SloBERTa | No | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top5_WithoutOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top10_WithoutOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top20_WithoutOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top50_WithoutOOC) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top100_WithoutOOC) | | BERT Multilingual | Yes | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top5_WithOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top10_WithOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top20_WithOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top50_WithOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top100_WithOOC_MultilingualBertBase) | | BERT Multilingual | No | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top5_WithoutOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top10_WithoutOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top20_WithoutOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top50_WithoutOOC_MultilingualBertBase) | [link](https://huggingface.co/gregorgabrovsek/SloBertAA_Top100_WithoutOOC_MultilingualBertBase) | Models fine-tuned on the IMDb datasets: | Base model | Includes the OOC class? | 5 classes | 10 classes | 25 classes | 50 classes | 100 classes | | ------------------- | ----------------------- |:---------:|:----------:|:----------:|:----------:|:-----------:| | BERT Multilingual | No | [link](https://huggingface.co/gregorgabrovsek/BERT_AA_IMDB_Top5_WithoutOOC_MultilingualBertBase) |[link](https://huggingface.co/gregorgabrovsek/BERT_AA_IMDB_Top10_WithoutOOC_MultilingualBertBase) |[link](https://huggingface.co/gregorgabrovsek/BERT_AA_IMDB_Top25_WithoutOOC_MultilingualBertBase) |[link](https://huggingface.co/gregorgabrovsek/BERT_AA_IMDB_Top50_WithoutOOC_MultilingualBertBase) |[link](https://huggingface.co/gregorgabrovsek/BERT_AA_IMDB_Top100_WithoutOOC_MultilingualBertBase) | ## 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: 2e-05 - train_batch_size: 12 - eval_batch_size: 12 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - num_epochs: 5 ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 0.4211 | 1.0 | 10508 | 0.3823 | 0.8700 | | 0.3163 | 2.0 | 21016 | 0.3917 | 0.8772 | | 0.257 | 3.0 | 31524 | 0.3771 | 0.8925 | | 0.1874 | 4.0 | 42032 | 0.5059 | 0.8931 | | 0.129 | 5.0 | 52540 | 0.5616 | 0.8946 | ### Framework versions - Transformers 4.26.1 - Pytorch 1.8.0 - Datasets 2.10.1 - Tokenizers 0.13.2