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bert_base_for_whole_train_result_Spam-Ham4_2
CatBarks/bert_base_for_whole_train_result_Spam-Ham4_2
bert_base_for_whole_train_result_Spam-Ham4_2 is a machine learning model from CatBarks. 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
- bert
- Access
- Public
- Created
- Feb 3, 2025
- Updated
- Feb 3, 2025
- SHA
- 375741a1
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. -->
bert_base_for_whole_train_result_Spam-Ham4_2
This model is a fine-tuned version of bert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0297
- Accuracy: 0.995
- F1: 0.9953
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 4096
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1000
- num_epochs: 100
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| 0.7353 | 6.8817 | 50 | 0.4382 | 0.8525 | 0.8511 |
| 0.2097 | 13.7634 | 100 | 0.0712 | 0.982 | 0.9830 |
| 0.0223 | 20.6452 | 150 | 0.0253 | 0.994 | 0.9944 |
| 0.0042 | 27.5269 | 200 | 0.0379 | 0.9915 | 0.9920 |
| 0.0018 | 34.4086 | 250 | 0.0323 | 0.995 | 0.9953 |
| 0.0008 | 41.2903 | 300 | 0.0350 | 0.994 | 0.9944 |
| 0.0038 | 48.1720 | 350 | 0.0344 | 0.993 | 0.9934 |
| 0.0014 | 55.0538 | 400 | 0.0310 | 0.995 | 0.9953 |
| 0.0003 | 61.9355 | 450 | 0.0314 | 0.9955 | 0.9958 |
| 0.0001 | 68.8172 | 500 | 0.0307 | 0.9945 | 0.9948 |
| 0.0001 | 75.6989 | 550 | 0.0380 | 0.994 | 0.9944 |
| 0.0001 | 82.5806 | 600 | 0.0375 | 0.9945 | 0.9948 |
| 0.0024 | 89.4624 | 650 | 0.0267 | 0.995 | 0.9953 |
| 0.0003 | 96.3441 | 700 | 0.0297 | 0.995 | 0.9953 |
Framework versions
- Transformers 4.40.0
- Pytorch 2.4.1+cu121
- Datasets 3.1.0
- Tokenizers 0.19.1
- Type
- bert
- License
- apache-2.0
- Created
- Feb 3, 2025
- Updated
- Feb 3, 2025