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RobertaBaseProcessedDownsampledKeywordDropoutE7
ImperialIndians23/RobertaBaseProcessedDownsampledKeywordDropoutE7
RobertaBaseProcessedDownsampledKeywordDropoutE7 is a machine learning model from ImperialIndians23. 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 mit.
should probably proofread and complete it, then remove this comment. --
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Public
Updated Mar 3, 2024
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At a glance
- License
- mit
- Access
- Public
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024
- SHA
- ef73f87f
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. -->
RobertaBaseProcessedDownsampledKeywordDropoutE7
This model is a fine-tuned version of roberta-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2529
- Accuracy: 0.8968
- F1: 0.4906
- Precision: 0.4622
- Recall: 0.5226
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: 1e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: inverse_sqrt
- lr_scheduler_warmup_steps: 500
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4823 | 1.0 | 297 | 0.5612 | 0.6734 | 0.3346 | 0.2075 | 0.8643 |
| 0.3851 | 2.0 | 595 | 0.2529 | 0.8968 | 0.4906 | 0.4622 | 0.5226 |
| 0.3502 | 3.0 | 893 | 0.3441 | 0.8567 | 0.4898 | 0.3702 | 0.7236 |
| 0.438 | 4.0 | 1191 | 0.4888 | 0.7822 | 0.4314 | 0.2869 | 0.8693 |
| 0.2282 | 5.0 | 1488 | 0.6598 | 0.8247 | 0.4611 | 0.3257 | 0.7889 |
| 0.2487 | 6.0 | 1786 | 0.6865 | 0.8558 | 0.4864 | 0.3676 | 0.7186 |
| 0.0087 | 6.98 | 2079 | 0.8314 | 0.8481 | 0.4854 | 0.3580 | 0.7538 |
Framework versions
- Transformers 4.38.2
- Pytorch 2.1.2+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2
- License
- mit
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024