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roberta-large_MBTI_P_MBTI_agg_balanced_75
DrinkIcedT/roberta-large_MBTI_P_MBTI_agg_balanced_75
roberta-large_MBTI_P_MBTI_agg_balanced_75 is a text classification model from DrinkIcedT. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Aug 11, 2026
- Updated
- Aug 11, 2026
- SHA
- e6dea101
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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. -->
roberta-large_MBTI_P_MBTI_agg_balanced_75
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.4700
- F1: 0.6600
- Threshold: 0.4400
- F1 At 05: 0.6568
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: 16
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 400
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Threshold | F1 At 05 |
|---|---|---|---|---|---|---|
| 2.7547 | 0.3509 | 200 | 2.7116 | 0.5595 | 0.5 | 0.5595 |
| 2.4978 | 0.7018 | 400 | 2.5463 | 0.6238 | 0.55 | 0.5913 |
| 2.3377 | 1.0526 | 600 | 2.4639 | 0.6456 | 0.4600 | 0.6306 |
| 2.2580 | 1.4035 | 800 | 2.4871 | 0.6570 | 0.47 | 0.6478 |
| 2.2076 | 1.7544 | 1000 | 2.4922 | 0.6615 | 0.49 | 0.6564 |
| 1.8098 | 2.1053 | 1200 | 2.6626 | 0.6660 | 0.47 | 0.6609 |
| 1.8935 | 2.4561 | 1400 | 2.6722 | 0.6566 | 0.48 | 0.6542 |
| 1.8169 | 2.8070 | 1600 | 2.6884 | 0.6568 | 0.49 | 0.6538 |
| 1.4062 | 3.1579 | 1800 | 2.9901 | 0.6602 | 0.4600 | 0.6566 |
| 1.4103 | 3.5088 | 2000 | 3.1019 | 0.6577 | 0.4600 | 0.6497 |
| 1.4479 | 3.8596 | 2200 | 3.1254 | 0.6574 | 0.47 | 0.6568 |
| 1.1628 | 4.2105 | 2400 | 3.3279 | 0.6591 | 0.47 | 0.6570 |
| 1.1744 | 4.5614 | 2600 | 3.3303 | 0.6601 | 0.4500 | 0.6554 |
| 1.0086 | 4.9123 | 2800 | 3.4700 | 0.6600 | 0.4400 | 0.6568 |
Framework versions
- Transformers 5.3.0
- Pytorch 2.7.1
- Datasets 4.8.5
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Aug 11, 2026
- Updated
- Aug 11, 2026