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distilbert-base-uncased-finetuned-items-multi-label1
chernandezc/distilbert-base-uncased-finetuned-items-multi-label1
distilbert-base-uncased-finetuned-items-multi-label1 is a text classification model from chernandezc. 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
- distilbert
- Access
- Public
- Created
- Nov 29, 2023
- Updated
- Nov 29, 2023
- SHA
- 79ed2ae4
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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. -->
distilbert-base-uncased-finetuned-items-multi-label1
This model is a fine-tuned version of distilbert-base-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3682
- F1 Micro: 0.7014
- F1 Macro: 0.6332
- Hamming Loss: 0.1497
- Jaccard Score: 0.4793
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: 30
- eval_batch_size: 30
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | Hamming Loss | Jaccard Score |
|---|---|---|---|---|---|---|---|
| 0.6037 | 1.0 | 32 | 0.5429 | 0.0 | 0.0 | 0.2816 | 0.0 |
| 0.5311 | 2.0 | 64 | 0.5032 | 0.0 | 0.0 | 0.2816 | 0.0 |
| 0.466 | 3.0 | 96 | 0.4669 | 0.3740 | 0.2279 | 0.2253 | 0.1587 |
| 0.4125 | 4.0 | 128 | 0.4320 | 0.4842 | 0.3553 | 0.2019 | 0.2393 |
| 0.3546 | 5.0 | 160 | 0.4026 | 0.5436 | 0.4311 | 0.1868 | 0.2992 |
| 0.3132 | 6.0 | 192 | 0.3856 | 0.5788 | 0.4574 | 0.1799 | 0.3264 |
| 0.2733 | 7.0 | 224 | 0.3747 | 0.6469 | 0.5372 | 0.1635 | 0.4001 |
| 0.2333 | 8.0 | 256 | 0.3695 | 0.6725 | 0.5476 | 0.1552 | 0.4098 |
| 0.2046 | 9.0 | 288 | 0.3586 | 0.6818 | 0.5559 | 0.1538 | 0.4161 |
| 0.1819 | 10.0 | 320 | 0.3578 | 0.6949 | 0.6108 | 0.1484 | 0.4566 |
| 0.1624 | 11.0 | 352 | 0.3649 | 0.6742 | 0.5884 | 0.1593 | 0.4345 |
| 0.1457 | 12.0 | 384 | 0.3565 | 0.6870 | 0.6134 | 0.1552 | 0.4593 |
| 0.1288 | 13.0 | 416 | 0.3592 | 0.6961 | 0.6263 | 0.1511 | 0.4733 |
| 0.1193 | 14.0 | 448 | 0.3682 | 0.6852 | 0.6097 | 0.1552 | 0.4577 |
| 0.1113 | 15.0 | 480 | 0.3643 | 0.6947 | 0.6215 | 0.1497 | 0.4704 |
| 0.1023 | 16.0 | 512 | 0.3652 | 0.6959 | 0.6265 | 0.1525 | 0.4740 |
| 0.0942 | 17.0 | 544 | 0.3730 | 0.6925 | 0.6262 | 0.1525 | 0.4726 |
| 0.0906 | 18.0 | 576 | 0.3687 | 0.7014 | 0.6372 | 0.1497 | 0.4825 |
| 0.0893 | 19.0 | 608 | 0.3657 | 0.7033 | 0.6317 | 0.1484 | 0.4797 |
| 0.0882 | 20.0 | 640 | 0.3682 | 0.7014 | 0.6332 | 0.1497 | 0.4793 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 29, 2023
- Updated
- Nov 29, 2023