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roberta-large_MBTI_N_MBTI_agg_balanced_50_1e-05_0.01
DrinkIcedT/roberta-large_MBTI_N_MBTI_agg_balanced_50_1e-05_0.01
roberta-large_MBTI_N_MBTI_agg_balanced_50_1e-05_0.01 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 18, 2026
- Updated
- Aug 18, 2026
- SHA
- 6c7f8608
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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_1e-05_0.01
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 4.4809
- F1: 0.6324
- Threshold: 0.59
- F1 At 05: 0.6288
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 |
|---|---|---|---|---|---|---|
| 2.0792 | 0.3175 | 200 | 2.5261 | 0.5293 | 0.62 | 0.4896 |
| 2.0783 | 0.6349 | 400 | 2.4215 | 0.5612 | 0.59 | 0.5119 |
| 1.9004 | 0.9524 | 600 | 2.3977 | 0.5910 | 0.54 | 0.5802 |
| 1.8296 | 1.2698 | 800 | 2.3046 | 0.6257 | 0.47 | 0.6250 |
| 1.6919 | 1.5873 | 1000 | 2.2716 | 0.6246 | 0.48 | 0.6220 |
| 1.6720 | 1.9048 | 1200 | 2.3439 | 0.6417 | 0.5 | 0.6417 |
| 1.3444 | 2.2222 | 1400 | 2.8271 | 0.6430 | 0.49 | 0.6426 |
| 1.3678 | 2.5397 | 1600 | 2.7147 | 0.6421 | 0.25 | 0.6293 |
| 1.2378 | 2.8571 | 1800 | 2.6890 | 0.6468 | 0.27 | 0.6256 |
| 0.8090 | 3.1746 | 2000 | 3.5935 | 0.6310 | 0.6800 | 0.6197 |
| 0.8144 | 3.4921 | 2200 | 3.2754 | 0.6458 | 0.25 | 0.6259 |
| 0.7820 | 3.8095 | 2400 | 3.4662 | 0.6383 | 0.49 | 0.6358 |
| 0.4995 | 4.1270 | 2600 | 4.3197 | 0.6311 | 0.73 | 0.6253 |
| 0.5583 | 4.4444 | 2800 | 4.4876 | 0.6261 | 0.78 | 0.6176 |
| 0.5347 | 4.7619 | 3000 | 4.4809 | 0.6324 | 0.59 | 0.6288 |
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 18, 2026
- Updated
- Aug 18, 2026