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memo_ND
yemen2016/memo_ND
memo_ND 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.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- xlm-roberta
- Access
- Public
- Created
- Jun 12, 2024
- Updated
- Jun 12, 2024
- SHA
- 6fc460c9
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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_ND
This model is a fine-tuned version of MiMe-MeMo/MeMo-BERT-03 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3100
- F1-score: 0.9021
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: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|---|---|---|---|---|
| No log | 1.0 | 223 | 0.3100 | 0.9021 |
| No log | 2.0 | 446 | 0.3473 | 0.8991 |
| 0.2918 | 3.0 | 669 | 0.5325 | 0.8914 |
| 0.2918 | 4.0 | 892 | 0.6119 | 0.8819 |
| 0.1085 | 5.0 | 1115 | 0.5423 | 0.8920 |
| 0.1085 | 6.0 | 1338 | 0.5977 | 0.8861 |
| 0.0701 | 7.0 | 1561 | 0.5991 | 0.8991 |
| 0.0701 | 8.0 | 1784 | 0.7600 | 0.8636 |
| 0.0381 | 9.0 | 2007 | 0.7346 | 0.8671 |
| 0.0381 | 10.0 | 2230 | 0.7637 | 0.8629 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.2
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Jun 12, 2024
- Updated
- Jun 12, 2024