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my_awesome_model
ruiminszb/my_awesome_model
my_awesome_model is a text classification model from ruiminszb. 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
- Jun 12, 2024
- Updated
- Jun 19, 2024
- SHA
- 0af94e2c
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Base models
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. -->
my_awesome_model
This model is a fine-tuned version of distilbert/distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0266
- Accuracy: 0.9963
- Recall: 0.8
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: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Recall |
|---|---|---|---|---|---|
| No log | 1.0 | 90 | 0.0396 | 0.9815 | 0.0 |
| No log | 2.0 | 180 | 0.0814 | 0.9815 | 0.0 |
| No log | 3.0 | 270 | 0.0400 | 0.9914 | 0.5333 |
| No log | 4.0 | 360 | 0.8444 | 0.6510 | 0.9333 |
| No log | 5.0 | 450 | 0.0246 | 0.9951 | 0.8667 |
| 0.0675 | 6.0 | 540 | 0.0686 | 0.9803 | 0.9333 |
| 0.0675 | 7.0 | 630 | 0.0205 | 0.9963 | 0.8667 |
| 0.0675 | 8.0 | 720 | 0.0163 | 0.9975 | 0.8667 |
| 0.0675 | 9.0 | 810 | 0.0183 | 0.9975 | 0.8667 |
| 0.0675 | 10.0 | 900 | 0.0274 | 0.9963 | 0.8 |
| 0.0675 | 11.0 | 990 | 0.0309 | 0.9951 | 0.7333 |
| 0.0107 | 12.0 | 1080 | 0.0268 | 0.9963 | 0.8 |
| 0.0107 | 13.0 | 1170 | 0.0203 | 0.9975 | 0.8667 |
| 0.0107 | 14.0 | 1260 | 0.0208 | 0.9975 | 0.8667 |
| 0.0107 | 15.0 | 1350 | 0.0230 | 0.9963 | 0.8 |
| 0.0107 | 16.0 | 1440 | 0.0301 | 0.9963 | 0.8 |
| 0.004 | 17.0 | 1530 | 0.0284 | 0.9963 | 0.8 |
| 0.004 | 18.0 | 1620 | 0.0282 | 0.9963 | 0.8 |
| 0.004 | 19.0 | 1710 | 0.0271 | 0.9963 | 0.8 |
| 0.004 | 20.0 | 1800 | 0.0266 | 0.9963 | 0.8 |
Framework versions
- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Jun 12, 2024
- Updated
- Jun 19, 2024