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roberta-large_MBTI_P_MBTI_agg_balanced_50
DrinkIcedT/roberta-large_MBTI_P_MBTI_agg_balanced_50
roberta-large_MBTI_P_MBTI_agg_balanced_50 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
- 5dad4389
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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_50
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.3548
- F1: 0.6448
- Threshold: 0.4500
- F1 At 05: 0.6386
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 |
|---|---|---|---|---|---|---|
| 2.7862 | 0.3175 | 200 | 2.7518 | 0.5559 | 0.51 | 0.5486 |
| 2.6301 | 0.6349 | 400 | 2.5925 | 0.6106 | 0.54 | 0.5781 |
| 2.5372 | 0.9524 | 600 | 2.5592 | 0.6188 | 0.6 | 0.5674 |
| 2.3286 | 1.2698 | 800 | 2.5031 | 0.6396 | 0.48 | 0.6361 |
| 2.3090 | 1.5873 | 1000 | 2.4561 | 0.6497 | 0.4300 | 0.6403 |
| 2.2343 | 1.9048 | 1200 | 2.4694 | 0.6516 | 0.4200 | 0.6380 |
| 1.9465 | 2.2222 | 1400 | 2.5517 | 0.6464 | 0.48 | 0.6380 |
| 1.9451 | 2.5397 | 1600 | 2.6020 | 0.6542 | 0.49 | 0.6513 |
| 1.9125 | 2.8571 | 1800 | 2.6197 | 0.6506 | 0.4600 | 0.6419 |
| 1.5855 | 3.1746 | 2000 | 2.8543 | 0.6496 | 0.47 | 0.6460 |
| 1.5699 | 3.4921 | 2200 | 3.0303 | 0.6533 | 0.4600 | 0.6507 |
| 1.5700 | 3.8095 | 2400 | 3.0547 | 0.6525 | 0.4600 | 0.6419 |
| 1.3236 | 4.1270 | 2600 | 3.1255 | 0.6512 | 0.37 | 0.6416 |
| 1.1587 | 4.4444 | 2800 | 3.3994 | 0.6474 | 0.4500 | 0.6435 |
| 1.1902 | 4.7619 | 3000 | 3.3548 | 0.6448 | 0.4500 | 0.6386 |
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