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distilbert-base-uncased_fold_2_ternary_v1
elopezlopez/distilbert-base-uncased_fold_2_ternary_v1
distilbert-base-uncased_fold_2_ternary_v1 is a text classification model from elopezlopez. 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
- Aug 2, 2022
- Updated
- Aug 2, 2022
- SHA
- 1b7174d7
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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. -->
distilbert-base-uncased_fold_2_ternary_v1
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: 1.8941
- F1: 0.7889
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: 25
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 |
|---|---|---|---|---|
| No log | 1.0 | 294 | 0.6025 | 0.7402 |
| 0.5688 | 2.0 | 588 | 0.5025 | 0.7943 |
| 0.5688 | 3.0 | 882 | 0.6102 | 0.7794 |
| 0.2582 | 4.0 | 1176 | 0.8896 | 0.7835 |
| 0.2582 | 5.0 | 1470 | 1.0392 | 0.7821 |
| 0.1185 | 6.0 | 1764 | 1.0865 | 0.7848 |
| 0.0461 | 7.0 | 2058 | 1.2951 | 0.7686 |
| 0.0461 | 8.0 | 2352 | 1.3348 | 0.7821 |
| 0.0313 | 9.0 | 2646 | 1.4267 | 0.7876 |
| 0.0313 | 10.0 | 2940 | 1.4004 | 0.7957 |
| 0.0142 | 11.0 | 3234 | 1.5501 | 0.7794 |
| 0.0083 | 12.0 | 3528 | 1.5564 | 0.7903 |
| 0.0083 | 13.0 | 3822 | 1.5699 | 0.7876 |
| 0.0067 | 14.0 | 4116 | 1.7725 | 0.7794 |
| 0.0067 | 15.0 | 4410 | 1.7642 | 0.7767 |
| 0.0031 | 16.0 | 4704 | 1.7891 | 0.7848 |
| 0.0031 | 17.0 | 4998 | 1.8528 | 0.7740 |
| 0.0054 | 18.0 | 5292 | 1.8378 | 0.7781 |
| 0.003 | 19.0 | 5586 | 1.8223 | 0.7862 |
| 0.003 | 20.0 | 5880 | 1.7935 | 0.7930 |
| 0.0021 | 21.0 | 6174 | 1.9117 | 0.7808 |
| 0.0021 | 22.0 | 6468 | 1.8891 | 0.7930 |
| 0.0015 | 23.0 | 6762 | 1.9167 | 0.7916 |
| 0.0006 | 24.0 | 7056 | 1.9193 | 0.7862 |
| 0.0006 | 25.0 | 7350 | 1.8941 | 0.7889 |
Framework versions
- Transformers 4.21.0
- Pytorch 1.12.0+cu113
- Datasets 2.4.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 2, 2022
- Updated
- Aug 2, 2022