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roberta-large_MBTI_N_MBTI_agg_balanced_50
DrinkIcedT/roberta-large_MBTI_N_MBTI_agg_balanced_50
roberta-large_MBTI_N_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 15, 2026
- Updated
- Aug 15, 2026
- SHA
- 5720c0d9
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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_N_MBTI_agg_balanced_50
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.1983
- F1: 0.6399
- Threshold: 0.71
- F1 At 05: 0.6356
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 |
|---|---|---|---|---|---|---|
| 2.0730 | 0.3175 | 200 | 2.5337 | 0.5345 | 0.59 | 0.4969 |
| 2.0878 | 0.6349 | 400 | 2.5395 | 0.5465 | 0.66 | 0.4823 |
| 1.9088 | 0.9524 | 600 | 2.3975 | 0.5796 | 0.58 | 0.5553 |
| 1.8219 | 1.2698 | 800 | 2.2591 | 0.6295 | 0.48 | 0.6246 |
| 1.6472 | 1.5873 | 1000 | 2.3102 | 0.6239 | 0.4600 | 0.6201 |
| 1.6390 | 1.9048 | 1200 | 2.3735 | 0.6425 | 0.48 | 0.6389 |
| 1.3419 | 2.2222 | 1400 | 2.5632 | 0.6346 | 0.6 | 0.6297 |
| 1.3172 | 2.5397 | 1600 | 2.6387 | 0.6376 | 0.4500 | 0.6289 |
| 1.2380 | 2.8571 | 1800 | 2.6161 | 0.6338 | 0.2900 | 0.6134 |
| 0.8433 | 3.1746 | 2000 | 3.5403 | 0.6289 | 0.61 | 0.6225 |
| 0.9017 | 3.4921 | 2200 | 3.3954 | 0.6410 | 0.36 | 0.6346 |
| 0.8778 | 3.8095 | 2400 | 3.2458 | 0.6400 | 0.4600 | 0.6372 |
| 0.4925 | 4.1270 | 2600 | 4.1601 | 0.6404 | 0.6800 | 0.6367 |
| 0.5520 | 4.4444 | 2800 | 4.1522 | 0.6360 | 0.4 | 0.6327 |
| 0.6119 | 4.7619 | 3000 | 4.1983 | 0.6399 | 0.71 | 0.6356 |
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 15, 2026
- Updated
- Aug 15, 2026