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distilbert-finetuned-disaster-entity
DipeshY/distilbert-finetuned-disaster-entity
distilbert-finetuned-disaster-entity is a token classification model from DipeshY. Use it when you need labels on individual words, such as names. 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
- Token Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Mar 16, 2023
- Updated
- Mar 16, 2023
- SHA
- 31b88d0e
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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. -->
fine_tune_results
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: 0.0821
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: 40
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 1 | 0.5517 |
| No log | 2.0 | 2 | 0.4685 |
| No log | 3.0 | 3 | 0.4025 |
| No log | 4.0 | 4 | 0.3522 |
| No log | 5.0 | 5 | 0.3154 |
| No log | 6.0 | 6 | 0.2895 |
| No log | 7.0 | 7 | 0.2715 |
| No log | 8.0 | 8 | 0.2579 |
| No log | 9.0 | 9 | 0.2464 |
| No log | 10.0 | 10 | 0.2362 |
| No log | 11.0 | 11 | 0.2270 |
| No log | 12.0 | 12 | 0.2188 |
| No log | 13.0 | 13 | 0.2114 |
| No log | 14.0 | 14 | 0.2049 |
| No log | 15.0 | 15 | 0.1988 |
| No log | 16.0 | 16 | 0.1926 |
| No log | 17.0 | 17 | 0.1862 |
| No log | 18.0 | 18 | 0.1793 |
| No log | 19.0 | 19 | 0.1720 |
| No log | 20.0 | 20 | 0.1644 |
| No log | 21.0 | 21 | 0.1565 |
| No log | 22.0 | 22 | 0.1485 |
| No log | 23.0 | 23 | 0.1406 |
| No log | 24.0 | 24 | 0.1330 |
| No log | 25.0 | 25 | 0.1259 |
| No log | 26.0 | 26 | 0.1193 |
| No log | 27.0 | 27 | 0.1133 |
| No log | 28.0 | 28 | 0.1080 |
| No log | 29.0 | 29 | 0.1032 |
| No log | 30.0 | 30 | 0.0991 |
| No log | 31.0 | 31 | 0.0955 |
| No log | 32.0 | 32 | 0.0925 |
| No log | 33.0 | 33 | 0.0900 |
| No log | 34.0 | 34 | 0.0878 |
| No log | 35.0 | 35 | 0.0860 |
| No log | 36.0 | 36 | 0.0847 |
| No log | 37.0 | 37 | 0.0836 |
| No log | 38.0 | 38 | 0.0828 |
| No log | 39.0 | 39 | 0.0823 |
| No log | 40.0 | 40 | 0.0821 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1+cpu
- Datasets 2.10.1
- Tokenizers 0.13.2
- Task
- Token Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Mar 16, 2023
- Updated
- Mar 16, 2023