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roberta-large_MBTI_P_MBTI_agg_balanced_50_1e-05
DrinkIcedT/roberta-large_MBTI_P_MBTI_agg_balanced_50_1e-05
roberta-large_MBTI_P_MBTI_agg_balanced_50_1e-05 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
- 46388968
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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_1e-05
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.5859
- F1: 0.6501
- Threshold: 0.4600
- F1 At 05: 0.6453
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 |
|---|---|---|---|---|---|---|
| 2.7917 | 0.3175 | 200 | 2.7551 | 0.5519 | 0.51 | 0.5055 |
| 2.7524 | 0.6349 | 400 | 2.6964 | 0.5847 | 0.48 | 0.5778 |
| 2.6408 | 0.9524 | 600 | 2.8801 | 0.6193 | 0.62 | 0.5743 |
| 2.3805 | 1.2698 | 800 | 2.5033 | 0.6433 | 0.4 | 0.6269 |
| 2.3284 | 1.5873 | 1000 | 2.4365 | 0.6562 | 0.4400 | 0.6383 |
| 2.2453 | 1.9048 | 1200 | 2.4504 | 0.6596 | 0.4500 | 0.6444 |
| 1.9319 | 2.2222 | 1400 | 2.5888 | 0.6569 | 0.49 | 0.6552 |
| 1.8355 | 2.5397 | 1600 | 2.5838 | 0.6589 | 0.4100 | 0.6498 |
| 1.8376 | 2.8571 | 1800 | 2.6546 | 0.6634 | 0.4500 | 0.6572 |
| 1.4069 | 3.1746 | 2000 | 3.2102 | 0.6561 | 0.47 | 0.6535 |
| 1.4559 | 3.4921 | 2200 | 3.1002 | 0.6516 | 0.48 | 0.6499 |
| 1.4083 | 3.8095 | 2400 | 3.3045 | 0.6506 | 0.4400 | 0.6482 |
| 1.1466 | 4.1270 | 2600 | 3.4599 | 0.6517 | 0.27 | 0.6455 |
| 1.0396 | 4.4444 | 2800 | 3.6286 | 0.6498 | 0.4300 | 0.6444 |
| 1.0788 | 4.7619 | 3000 | 3.5859 | 0.6501 | 0.4600 | 0.6453 |
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