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roberta-large_MBTI_F_MBTI_agg_balanced_50_2e-05
DrinkIcedT/roberta-large_MBTI_F_MBTI_agg_balanced_50_2e-05
roberta-large_MBTI_F_MBTI_agg_balanced_50_2e-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
- ecfc17b5
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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_50_2e-05
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 5.2280
- F1: 0.7453
- Threshold: 0.7
- F1 At 05: 0.7395
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: 2e-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 |
|---|---|---|---|---|---|---|
| 2.2564 | 0.3175 | 200 | 2.2785 | 0.7009 | 0.51 | 0.6975 |
| 2.2209 | 0.6349 | 400 | 2.1052 | 0.7376 | 0.49 | 0.7328 |
| 1.9265 | 0.9524 | 600 | 2.1296 | 0.7419 | 0.64 | 0.7261 |
| 1.6516 | 1.2698 | 800 | 2.1465 | 0.7524 | 0.28 | 0.7392 |
| 1.5346 | 1.5873 | 1000 | 2.2212 | 0.7459 | 0.6800 | 0.7436 |
| 1.4403 | 1.9048 | 1200 | 2.2808 | 0.7454 | 0.66 | 0.7360 |
| 0.8753 | 2.2222 | 1400 | 2.5984 | 0.7430 | 0.53 | 0.7407 |
| 0.9091 | 2.5397 | 1600 | 2.7683 | 0.7469 | 0.52 | 0.7468 |
| 0.7780 | 2.8571 | 1800 | 2.8194 | 0.7423 | 0.4500 | 0.7396 |
| 0.4435 | 3.1746 | 2000 | 3.5207 | 0.7422 | 0.4600 | 0.7404 |
| 0.4417 | 3.4921 | 2200 | 3.5814 | 0.7377 | 0.59 | 0.7360 |
| 0.3913 | 3.8095 | 2400 | 3.7803 | 0.7417 | 0.6 | 0.7396 |
| 0.2036 | 4.1270 | 2600 | 4.6824 | 0.7379 | 0.11 | 0.7353 |
| 0.2582 | 4.4444 | 2800 | 4.9114 | 0.7397 | 0.78 | 0.7373 |
| 0.2030 | 4.7619 | 3000 | 5.2280 | 0.7453 | 0.7 | 0.7395 |
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