Downloads · 30 days
8
1% of all-time downloads
distil-slovakbert-upos
crabz/distil-slovakbert-upos
distil-slovakbert-upos is a token classification model from crabz. Use it when you need labels on individual words, such as names. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
All-time downloads
1K
Public
Repo size
652 MB
Likes
0
Public
Repo makeup
Click a slice to open those files.
.bin326 MB · 99%
At a glance
- Task
- Token Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Mar 5, 2022
- Updated
- Mar 6, 2022
- SHA
- 9156f9ef
Try a prompt
Datasets
Model card
From the Hugging Face model README
<!-- 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. -->
distil-slovakbert-upos
This model is a fine-tuned version of crabz/distil-slovakbert on the universal_dependencies sk_snk dataset. It achieves the following results on the evaluation set:
- Loss: 0.1207
- Precision: 0.9771
- Recall: 0.9785
- F1: 0.9778
- Accuracy: 0.9801
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: 5e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 266 | 0.2168 | 0.9570 | 0.9554 | 0.9562 | 0.9610 |
| 0.3935 | 2.0 | 532 | 0.1416 | 0.9723 | 0.9736 | 0.9730 | 0.9740 |
| 0.3935 | 3.0 | 798 | 0.1236 | 0.9722 | 0.9735 | 0.9728 | 0.9747 |
| 0.0664 | 4.0 | 1064 | 0.1195 | 0.9722 | 0.9741 | 0.9732 | 0.9766 |
| 0.0664 | 5.0 | 1330 | 0.1160 | 0.9764 | 0.9772 | 0.9768 | 0.9789 |
| 0.0377 | 6.0 | 1596 | 0.1194 | 0.9763 | 0.9776 | 0.9770 | 0.9790 |
| 0.0377 | 7.0 | 1862 | 0.1188 | 0.9740 | 0.9755 | 0.9748 | 0.9777 |
| 0.024 | 8.0 | 2128 | 0.1188 | 0.9762 | 0.9777 | 0.9769 | 0.9793 |
| 0.024 | 9.0 | 2394 | 0.1207 | 0.9774 | 0.9789 | 0.9781 | 0.9802 |
| 0.0184 | 10.0 | 2660 | 0.1207 | 0.9771 | 0.9785 | 0.9778 | 0.9801 |
Framework versions
- Transformers 4.17.0.dev0
- Pytorch 1.10.0
- Datasets 1.16.1
- Tokenizers 0.11.0
- Task
- Token Classification
- Library
- transformers
- Type
- roberta
- Created
- Mar 5, 2022
- Updated
- Mar 6, 2022