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memobert_NC
yemen2016/memobert_NC
memobert_NC 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
- Jul 4, 2024
- Updated
- Jul 4, 2024
- SHA
- 4fa24820
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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. -->
memobert_NC
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: 0.3259
- F1-score: 0.8947
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: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | F1-score |
|---|---|---|---|---|
| No log | 1.0 | 40 | 0.3862 | 0.7719 |
| No log | 2.0 | 80 | 0.3259 | 0.8947 |
| No log | 3.0 | 120 | 0.3613 | 0.8725 |
| No log | 4.0 | 160 | 0.3348 | 0.8947 |
| No log | 5.0 | 200 | 0.4362 | 0.8615 |
| No log | 6.0 | 240 | 0.3633 | 0.8902 |
| No log | 7.0 | 280 | 0.3475 | 0.8921 |
| No log | 8.0 | 320 | 0.4318 | 0.8835 |
| No log | 9.0 | 360 | 0.4266 | 0.8812 |
| No log | 10.0 | 400 | 0.4330 | 0.8902 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- Created
- Jul 4, 2024
- Updated
- Jul 4, 2024