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WITHINAPPS_NDD-dimeshift_test-content-CwAdj_EntireRepresentations
lgk03/WITHINAPPS_NDD-dimeshift_test-content-CwAdj_EntireRepresentations
WITHINAPPS_NDD-dimeshift_test-content-CwAdj_EntireRepresentations is a machine learning model from lgk03. Use it for the machine learning task on the model card, and read the license before you ship it in a product. 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
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024
- SHA
- deff80e8
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. -->
WITHINAPPS_NDD-dimeshift_test-content-CwAdj_EntireRepresentations
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: 0.5885
- Accuracy: 0.5404
- F1: 0.6364
- Precision: 0.9173
- Recall: 0.5404
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| No log | 0.9897 | 36 | 0.7413 | 0.0795 | 0.0117 | 0.0063 | 0.0795 |
| No log | 1.9794 | 72 | 0.6924 | 0.3865 | 0.4814 | 0.9056 | 0.3865 |
| No log | 2.9966 | 109 | 0.6657 | 0.4665 | 0.5674 | 0.9045 | 0.4665 |
| No log | 3.9863 | 145 | 0.6637 | 0.4282 | 0.5267 | 0.9099 | 0.4282 |
| No log | 4.9759 | 181 | 0.6404 | 0.4794 | 0.5790 | 0.9121 | 0.4794 |
| No log | 5.9931 | 218 | 0.6189 | 0.5469 | 0.6429 | 0.9118 | 0.5469 |
| No log | 6.9828 | 254 | 0.6017 | 0.5477 | 0.6433 | 0.9151 | 0.5477 |
| No log | 8.0 | 291 | 0.5944 | 0.5413 | 0.6373 | 0.9165 | 0.5413 |
| No log | 8.9897 | 327 | 0.5910 | 0.5537 | 0.6489 | 0.9138 | 0.5537 |
| No log | 9.8969 | 360 | 0.5885 | 0.5404 | 0.6364 | 0.9173 | 0.5404 |
Framework versions
- Transformers 4.43.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 6, 2024
- Updated
- Aug 6, 2024