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edos-2023-baseline-bert-base-uncased-label_vector
lct-rug-2022/edos-2023-baseline-bert-base-uncased-label_vector
edos-2023-baseline-bert-base-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
- bee0eb44
Try a prompt
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-uncased-label_vector
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5258
- F1: 0.2606
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 |
|---|---|---|---|---|
| 2.1324 | 1.18 | 100 | 1.9573 | 0.0997 |
| 1.8322 | 2.35 | 200 | 1.8104 | 0.1286 |
| 1.6653 | 3.53 | 300 | 1.7238 | 0.1577 |
| 1.5292 | 4.71 | 400 | 1.6735 | 0.1655 |
| 1.423 | 5.88 | 500 | 1.5987 | 0.1916 |
| 1.2936 | 7.06 | 600 | 1.5628 | 0.2359 |
| 1.2256 | 8.24 | 700 | 1.5492 | 0.2496 |
| 1.1385 | 9.41 | 800 | 1.5388 | 0.2618 |
| 1.1138 | 10.59 | 900 | 1.5233 | 0.2678 |
| 1.0599 | 11.76 | 1000 | 1.5258 | 0.2606 |
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