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edos-2023-baseline-bert-base-multilingual-uncased-label_vector
lct-rug-2022/edos-2023-baseline-bert-base-multilingual-uncased-label_vector
edos-2023-baseline-bert-base-multilingual-uncased-label_vector is a text classification model from lct-rug-2022. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- bert
- Access
- Public
- Created
- Nov 28, 2022
- Updated
- Nov 29, 2022
- SHA
- fa444441
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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. -->
edos-2023-baseline-bert-base-multilingual-uncased-label_vector
This model is a fine-tuned version of bert-base-multilingual-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6113
- F1: 0.2785
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: 1e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 5
- num_epochs: 12
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| 2.0125 | 1.18 | 100 | 1.8290 | 0.1089 |
| 1.6698 | 2.35 | 200 | 1.6458 | 0.2223 |
| 1.4812 | 3.53 | 300 | 1.6035 | 0.2463 |
| 1.3137 | 4.71 | 400 | 1.5729 | 0.2502 |
| 1.2143 | 5.88 | 500 | 1.5549 | 0.2697 |
| 1.0805 | 7.06 | 600 | 1.5553 | 0.2759 |
| 0.9838 | 8.24 | 700 | 1.5730 | 0.2879 |
| 0.8981 | 9.41 | 800 | 1.6113 | 0.2785 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.1
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 28, 2022
- Updated
- Nov 29, 2022