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MeMo_BERT-WSD-ScandiBERT
yemen2016/MeMo_BERT-WSD-ScandiBERT
MeMo_BERT-WSD-ScandiBERT is a text classification model from yemen2016. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as agpl-3.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- agpl-3.0
- Model type
- xlm-roberta
- Access
- Public
- Created
- Mar 19, 2024
- Updated
- Mar 19, 2024
- SHA
- 32b99f8e
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Base models
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. -->
MeMo_BERT-WSD-ScandiBERT
This model is a fine-tuned version of vesteinn/ScandiBERT on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.0491
- F1-score: 0.4001
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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|---|---|---|---|---|
| No log | 1.0 | 61 | 1.3760 | 0.1229 |
| No log | 2.0 | 122 | 1.4064 | 0.1229 |
| No log | 3.0 | 183 | 1.4753 | 0.1229 |
| No log | 4.0 | 244 | 1.3255 | 0.1229 |
| No log | 5.0 | 305 | 1.3649 | 0.1229 |
| No log | 6.0 | 366 | 1.3784 | 0.1229 |
| No log | 7.0 | 427 | 1.3312 | 0.2191 |
| No log | 8.0 | 488 | 1.3717 | 0.1229 |
| 1.2808 | 9.0 | 549 | 1.5063 | 0.1229 |
| 1.2808 | 10.0 | 610 | 1.2576 | 0.3721 |
| 1.2808 | 11.0 | 671 | 1.4630 | 0.3622 |
| 1.2808 | 12.0 | 732 | 1.7778 | 0.3258 |
| 1.2808 | 13.0 | 793 | 2.2233 | 0.3402 |
| 1.2808 | 14.0 | 854 | 2.1684 | 0.3619 |
| 1.2808 | 15.0 | 915 | 2.0034 | 0.3668 |
| 1.2808 | 16.0 | 976 | 1.8374 | 0.3818 |
| 0.9251 | 17.0 | 1037 | 1.9104 | 0.3956 |
| 0.9251 | 18.0 | 1098 | 2.0491 | 0.4001 |
| 0.9251 | 19.0 | 1159 | 2.1429 | 0.3534 |
| 0.9251 | 20.0 | 1220 | 2.1352 | 0.3648 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- agpl-3.0
- Created
- Mar 19, 2024
- Updated
- Mar 19, 2024