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tsBERT_sa_cv_9_fold2
DiederikMartens/tsBERT_sa_cv_9_fold2
tsBERT_sa_cv_9_fold2 is a text classification model from DiederikMartens. 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
- bert
- Access
- Public
- Created
- May 28, 2024
- Updated
- May 28, 2024
- SHA
- fed34210
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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. -->
tsBERT_sa_cv_9_fold2
This model is a fine-tuned version of igorsterner/german-english-code-switching-bert on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4460
- F1: 0.6894
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: 4.47e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 325 | 0.4309 | 0.5828 |
| 0.4351 | 2.0 | 650 | 0.4460 | 0.6894 |
| 0.4351 | 3.0 | 975 | 0.5855 | 0.6810 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- May 28, 2024
- Updated
- May 28, 2024