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distilbert-base-uncased_fold_6_binary
elopezlopez/distilbert-base-uncased_fold_6_binary
distilbert-base-uncased_fold_6_binary 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
- Jul 31, 2022
- Updated
- Jul 31, 2022
- SHA
- 4d14fc54
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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_6_binary
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: 1.6838
- F1: 0.7881
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 | 290 | 0.4181 | 0.7732 |
| 0.4097 | 2.0 | 580 | 0.3967 | 0.7697 |
| 0.4097 | 3.0 | 870 | 0.5811 | 0.7797 |
| 0.2034 | 4.0 | 1160 | 0.8684 | 0.7320 |
| 0.2034 | 5.0 | 1450 | 0.9116 | 0.7718 |
| 0.0794 | 6.0 | 1740 | 1.0588 | 0.7690 |
| 0.0278 | 7.0 | 2030 | 1.2092 | 0.7738 |
| 0.0278 | 8.0 | 2320 | 1.2180 | 0.7685 |
| 0.0233 | 9.0 | 2610 | 1.3005 | 0.7676 |
| 0.0233 | 10.0 | 2900 | 1.4009 | 0.7634 |
| 0.0093 | 11.0 | 3190 | 1.4528 | 0.7805 |
| 0.0093 | 12.0 | 3480 | 1.4803 | 0.7859 |
| 0.0088 | 13.0 | 3770 | 1.4775 | 0.7750 |
| 0.0077 | 14.0 | 4060 | 1.6171 | 0.7699 |
| 0.0077 | 15.0 | 4350 | 1.6429 | 0.7636 |
| 0.0047 | 16.0 | 4640 | 1.5619 | 0.7819 |
| 0.0047 | 17.0 | 4930 | 1.5833 | 0.7724 |
| 0.0034 | 18.0 | 5220 | 1.6400 | 0.7853 |
| 0.0008 | 19.0 | 5510 | 1.6508 | 0.7792 |
| 0.0008 | 20.0 | 5800 | 1.6838 | 0.7881 |
| 0.0009 | 21.0 | 6090 | 1.6339 | 0.7829 |
| 0.0009 | 22.0 | 6380 | 1.6824 | 0.7806 |
| 0.0016 | 23.0 | 6670 | 1.6867 | 0.7876 |
| 0.0016 | 24.0 | 6960 | 1.7107 | 0.7877 |
| 0.0013 | 25.0 | 7250 | 1.6933 | 0.7812 |
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
- Jul 31, 2022
- Updated
- Jul 31, 2022