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WITHINAPPS_NDD-ppma_test-content-CwAdj_EntireRepresentations
lgk03/WITHINAPPS_NDD-ppma_test-content-CwAdj_EntireRepresentations
WITHINAPPS_NDD-ppma_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 2, 2024
- Updated
- Aug 2, 2024
- SHA
- 913ae5dd
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-ppma_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: 0.3966
- Accuracy: 0.8383
- F1: 0.8578
- Precision: 0.8972
- Recall: 0.8383
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 | 0.9836 | 15 | 0.6703 | 0.3048 | 0.3447 | 0.8520 | 0.3048 |
| No log | 1.9672 | 30 | 0.5924 | 0.6231 | 0.6883 | 0.8726 | 0.6231 |
| No log | 2.9508 | 45 | 0.5599 | 0.6529 | 0.7135 | 0.8745 | 0.6529 |
| No log | 4.0 | 61 | 0.5139 | 0.7209 | 0.7681 | 0.8805 | 0.7209 |
| No log | 4.9836 | 76 | 0.4743 | 0.7909 | 0.8210 | 0.8827 | 0.7909 |
| No log | 5.9672 | 91 | 0.4791 | 0.7539 | 0.7935 | 0.8827 | 0.7539 |
| No log | 6.9508 | 106 | 0.4418 | 0.7858 | 0.8177 | 0.8856 | 0.7858 |
| No log | 8.0 | 122 | 0.4102 | 0.8218 | 0.8452 | 0.8931 | 0.8218 |
| No log | 8.9836 | 137 | 0.3967 | 0.8445 | 0.8624 | 0.8976 | 0.8445 |
| No log | 9.8361 | 150 | 0.3966 | 0.8383 | 0.8578 | 0.8972 | 0.8383 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Type
- distilbert
- License
- apache-2.0
- Created
- Aug 2, 2024
- Updated
- Aug 2, 2024