SloBertAA_Top5_WithOOC
This model is a fine-tuned version of 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 | link | link | link | link |
| SloBERTa | No | link | link | link | link | link |
| BERT Multilingual | Yes | link | link | link | link | link |
| BERT Multilingual | No | link | link | link | link | link |
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 | link | link | link | link |
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
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