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afro-xlmr-base-vmw-MICRO
sercetexam9/afro-xlmr-base-vmw-MICRO
afro-xlmr-base-vmw-MICRO is a text classification model from sercetexam9. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jan 31, 2025
- Updated
- Jan 31, 2025
- SHA
- 7e821299
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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. -->
afro-xlmr-base-vmw-MICRO
This model is a fine-tuned version of Davlan/afro-xlmr-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3214
- F1: 0.3409
- Roc Auc: 0.6282
- Accuracy: 0.5300
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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Roc Auc | Accuracy |
|---|---|---|---|---|---|---|
| 0.2701 | 1.0 | 146 | 0.2659 | 0.0 | 0.5 | 0.5164 |
| 0.2597 | 2.0 | 292 | 0.2704 | 0.0 | 0.5 | 0.5164 |
| 0.2792 | 3.0 | 438 | 0.2623 | 0.0 | 0.5 | 0.5164 |
| 0.2183 | 4.0 | 584 | 0.2583 | 0.0534 | 0.5136 | 0.5280 |
| 0.2156 | 5.0 | 730 | 0.2518 | 0.1701 | 0.5466 | 0.5513 |
| 0.1805 | 6.0 | 876 | 0.2535 | 0.2421 | 0.5737 | 0.5416 |
| 0.156 | 7.0 | 1022 | 0.2597 | 0.2715 | 0.5863 | 0.5474 |
| 0.1261 | 8.0 | 1168 | 0.2728 | 0.2717 | 0.5846 | 0.5571 |
| 0.1157 | 9.0 | 1314 | 0.2882 | 0.3146 | 0.6135 | 0.5164 |
| 0.0977 | 10.0 | 1460 | 0.2980 | 0.3073 | 0.6097 | 0.5184 |
| 0.0762 | 11.0 | 1606 | 0.3144 | 0.2925 | 0.6031 | 0.5126 |
| 0.0669 | 12.0 | 1752 | 0.3256 | 0.3333 | 0.6275 | 0.5106 |
| 0.0591 | 13.0 | 1898 | 0.3214 | 0.3409 | 0.6282 | 0.5300 |
| 0.0461 | 14.0 | 2044 | 0.3286 | 0.3357 | 0.6226 | 0.5358 |
| 0.0567 | 15.0 | 2190 | 0.3313 | 0.3248 | 0.6190 | 0.5222 |
| 0.0495 | 16.0 | 2336 | 0.3397 | 0.3102 | 0.6124 | 0.5145 |
| 0.0363 | 17.0 | 2482 | 0.3370 | 0.3110 | 0.6106 | 0.5300 |
Framework versions
- Transformers 4.45.1
- Pytorch 2.4.0
- Datasets 3.0.1
- Tokenizers 0.20.0
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jan 31, 2025
- Updated
- Jan 31, 2025