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roberta-large_MBTI_F_MBTI_agg_balanced_75
DrinkIcedT/roberta-large_MBTI_F_MBTI_agg_balanced_75
roberta-large_MBTI_F_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
- 1b9237af
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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_F_MBTI_agg_balanced_75
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.2707
- F1: 0.7424
- Threshold: 0.4300
- F1 At 05: 0.7402
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 |
|---|---|---|---|---|---|---|
| 2.3038 | 0.3509 | 200 | 2.4180 | 0.6890 | 0.7 | 0.6766 |
| 2.0894 | 0.7018 | 400 | 2.1384 | 0.7274 | 0.47 | 0.7236 |
| 1.8962 | 1.0526 | 600 | 2.2237 | 0.7368 | 0.59 | 0.7262 |
| 1.7857 | 1.4035 | 800 | 1.9827 | 0.7569 | 0.4300 | 0.7546 |
| 1.5800 | 1.7544 | 1000 | 2.0766 | 0.7486 | 0.4300 | 0.7455 |
| 1.1423 | 2.1053 | 1200 | 2.3144 | 0.7532 | 0.49 | 0.7530 |
| 1.1359 | 2.4561 | 1400 | 2.4229 | 0.7456 | 0.5 | 0.7456 |
| 1.2092 | 2.8070 | 1600 | 2.3130 | 0.7450 | 0.4100 | 0.7422 |
| 0.7618 | 3.1579 | 1800 | 2.7125 | 0.7437 | 0.37 | 0.7411 |
| 0.7598 | 3.5088 | 2000 | 2.7720 | 0.7389 | 0.58 | 0.7370 |
| 0.7066 | 3.8596 | 2200 | 2.8773 | 0.7458 | 0.36 | 0.7413 |
| 0.4746 | 4.2105 | 2400 | 3.4122 | 0.7400 | 0.64 | 0.7353 |
| 0.4844 | 4.5614 | 2600 | 3.3015 | 0.7409 | 0.49 | 0.7393 |
| 0.4933 | 4.9123 | 2800 | 3.2707 | 0.7424 | 0.4300 | 0.7402 |
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