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distilbert-base-uncased_fold_3_ternary
elopezlopez/distilbert-base-uncased_fold_3_ternary
distilbert-base-uncased_fold_3_ternary 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
- d6c5a620
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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_3_ternary
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: 1.7987
- F1: 0.7460
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 | 289 | 0.5903 | 0.6893 |
| 0.5417 | 2.0 | 578 | 0.5822 | 0.7130 |
| 0.5417 | 3.0 | 867 | 0.6471 | 0.7385 |
| 0.2298 | 4.0 | 1156 | 0.8933 | 0.7322 |
| 0.2298 | 5.0 | 1445 | 1.1002 | 0.7147 |
| 0.1012 | 6.0 | 1734 | 1.2041 | 0.7249 |
| 0.0508 | 7.0 | 2023 | 1.3575 | 0.7195 |
| 0.0508 | 8.0 | 2312 | 1.3896 | 0.7385 |
| 0.018 | 9.0 | 2601 | 1.5363 | 0.7238 |
| 0.018 | 10.0 | 2890 | 1.5336 | 0.7364 |
| 0.0142 | 11.0 | 3179 | 1.6335 | 0.7308 |
| 0.0142 | 12.0 | 3468 | 1.6915 | 0.7295 |
| 0.0047 | 13.0 | 3757 | 1.7087 | 0.7427 |
| 0.0058 | 14.0 | 4046 | 1.7875 | 0.7378 |
| 0.0058 | 15.0 | 4335 | 1.7649 | 0.7438 |
| 0.0051 | 16.0 | 4624 | 1.7987 | 0.7460 |
| 0.0051 | 17.0 | 4913 | 1.8435 | 0.7404 |
| 0.0025 | 18.0 | 5202 | 1.9623 | 0.7257 |
| 0.0025 | 19.0 | 5491 | 1.9005 | 0.7304 |
| 0.0029 | 20.0 | 5780 | 1.9437 | 0.7374 |
| 0.0011 | 21.0 | 6069 | 1.9840 | 0.7268 |
| 0.0011 | 22.0 | 6358 | 1.9411 | 0.7346 |
| 0.0025 | 23.0 | 6647 | 1.9233 | 0.7438 |
| 0.0025 | 24.0 | 6936 | 1.9415 | 0.7395 |
| 0.0015 | 25.0 | 7225 | 1.9481 | 0.7411 |
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