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augmented_model_fast_4_b_3e6batch16
LeonardoFettucciari/augmented_model_fast_4_b_3e6batch16
augmented_model_fast_4_b_3e6batch16 is a text classification model from LeonardoFettucciari. 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 18, 2024
- Updated
- Jun 18, 2024
- SHA
- e86ab129
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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. -->
augmented_model_fast_4_b_3e6batch16
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2149
- Accuracy: 0.5193
- F1: 0.5214
- Precision: 0.5244
- Recall: 0.5196
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: 3e-06
- train_batch_size: 16
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.567 | 0.1566 | 500 | 0.9748 | 0.6385 | 0.6316 | 0.6368 | 0.6321 |
| 0.6834 | 0.3133 | 1000 | 0.8564 | 0.6556 | 0.6458 | 0.6506 | 0.6474 |
| 0.6231 | 0.4699 | 1500 | 0.8447 | 0.6600 | 0.6517 | 0.6555 | 0.6526 |
| 0.6625 | 0.6266 | 2000 | 0.8117 | 0.6648 | 0.6574 | 0.6608 | 0.6579 |
| 0.6663 | 0.7832 | 2500 | 0.7971 | 0.6709 | 0.6634 | 0.6657 | 0.6640 |
| 0.6581 | 0.9398 | 3000 | 0.7967 | 0.6753 | 0.6674 | 0.6693 | 0.6682 |
| 0.5847 | 1.0965 | 3500 | 0.8181 | 0.6792 | 0.6707 | 0.6730 | 0.6717 |
| 0.5453 | 1.2531 | 4000 | 0.8346 | 0.6831 | 0.6743 | 0.6774 | 0.6755 |
| 0.5543 | 1.4098 | 4500 | 0.8275 | 0.6831 | 0.6739 | 0.6766 | 0.6753 |
| 0.5469 | 1.5664 | 5000 | 0.8255 | 0.6836 | 0.6754 | 0.6782 | 0.6763 |
| 0.5248 | 1.7231 | 5500 | 0.8275 | 0.6849 | 0.6757 | 0.6782 | 0.6771 |
| 0.5603 | 1.8797 | 6000 | 0.8228 | 0.6844 | 0.6752 | 0.6777 | 0.6766 |
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 18, 2024
- Updated
- Jun 18, 2024