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roberta-large_MBTI_P_MBTI_agg_balanced_50_5e-06
DrinkIcedT/roberta-large_MBTI_P_MBTI_agg_balanced_50_5e-06
roberta-large_MBTI_P_MBTI_agg_balanced_50_5e-06 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 17, 2026
- Updated
- Aug 17, 2026
- SHA
- 8aef2755
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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_5e-06
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.9228
- F1: 0.6532
- Threshold: 0.4600
- F1 At 05: 0.6506
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: 5e-06
- 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 |
|---|---|---|---|---|---|---|
| 2.7823 | 0.3175 | 200 | 2.7641 | 0.5404 | 0.49 | 0.5091 |
| 2.6580 | 0.6349 | 400 | 2.6040 | 0.6100 | 0.53 | 0.6044 |
| 2.5028 | 0.9524 | 600 | 2.4980 | 0.6334 | 0.53 | 0.6147 |
| 2.3553 | 1.2698 | 800 | 2.4623 | 0.6414 | 0.4200 | 0.6382 |
| 2.3278 | 1.5873 | 1000 | 2.4547 | 0.6466 | 0.48 | 0.6358 |
| 2.2641 | 1.9048 | 1200 | 2.4881 | 0.6550 | 0.5 | 0.6550 |
| 2.0946 | 2.2222 | 1400 | 2.5079 | 0.6537 | 0.5 | 0.6537 |
| 2.0024 | 2.5397 | 1600 | 2.6318 | 0.6567 | 0.49 | 0.6538 |
| 2.0089 | 2.8571 | 1800 | 2.6125 | 0.6572 | 0.4600 | 0.6559 |
| 1.8590 | 3.1746 | 2000 | 2.6819 | 0.6528 | 0.4300 | 0.6437 |
| 1.8145 | 3.4921 | 2200 | 2.7451 | 0.6555 | 0.4500 | 0.6506 |
| 1.8041 | 3.8095 | 2400 | 2.7587 | 0.6544 | 0.4500 | 0.6517 |
| 1.6612 | 4.1270 | 2600 | 2.8055 | 0.6546 | 0.4600 | 0.6497 |
| 1.5591 | 4.4444 | 2800 | 2.9453 | 0.6522 | 0.48 | 0.6493 |
| 1.5398 | 4.7619 | 3000 | 2.9228 | 0.6532 | 0.4600 | 0.6506 |
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 17, 2026
- Updated
- Aug 17, 2026