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distilbert-base-uncased_fold_7_ternary_v1
elopezlopez/distilbert-base-uncased_fold_7_ternary_v1
distilbert-base-uncased_fold_7_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
- 0f244e19
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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_7_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: 2.0462
- F1: 0.7836
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 | 291 | 0.5719 | 0.7490 |
| 0.5541 | 2.0 | 582 | 0.5563 | 0.7836 |
| 0.5541 | 3.0 | 873 | 0.7301 | 0.7849 |
| 0.2509 | 4.0 | 1164 | 0.8073 | 0.7926 |
| 0.2509 | 5.0 | 1455 | 1.0842 | 0.7823 |
| 0.1182 | 6.0 | 1746 | 1.1721 | 0.7900 |
| 0.0537 | 7.0 | 2037 | 1.4060 | 0.7785 |
| 0.0537 | 8.0 | 2328 | 1.4497 | 0.7836 |
| 0.0262 | 9.0 | 2619 | 1.4722 | 0.7708 |
| 0.0262 | 10.0 | 2910 | 1.6529 | 0.7772 |
| 0.0131 | 11.0 | 3201 | 1.6573 | 0.7862 |
| 0.0131 | 12.0 | 3492 | 1.6986 | 0.7823 |
| 0.0115 | 13.0 | 3783 | 1.7765 | 0.7810 |
| 0.0098 | 14.0 | 4074 | 1.8036 | 0.7862 |
| 0.0098 | 15.0 | 4365 | 1.7684 | 0.7926 |
| 0.0028 | 16.0 | 4656 | 1.8385 | 0.7836 |
| 0.0028 | 17.0 | 4947 | 1.7903 | 0.7887 |
| 0.0054 | 18.0 | 5238 | 1.9065 | 0.7810 |
| 0.0007 | 19.0 | 5529 | 1.9331 | 0.7875 |
| 0.0007 | 20.0 | 5820 | 1.9384 | 0.7849 |
| 0.0006 | 21.0 | 6111 | 1.8687 | 0.7887 |
| 0.0006 | 22.0 | 6402 | 2.0603 | 0.7785 |
| 0.0009 | 23.0 | 6693 | 2.0403 | 0.7836 |
| 0.0009 | 24.0 | 6984 | 2.0348 | 0.7810 |
| 0.0005 | 25.0 | 7275 | 2.0462 | 0.7836 |
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