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roberta-large_MBTI_N_MBTI_agg_balanced_50_5e-06
DrinkIcedT/roberta-large_MBTI_N_MBTI_agg_balanced_50_5e-06
roberta-large_MBTI_N_MBTI_agg_balanced_50_5e-06 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
- e49c14b6
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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_5e-06
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 3.1652
- F1: 0.6345
- Threshold: 0.5700
- F1 At 05: 0.6295
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: 5e-06
- 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 |
|---|---|---|---|---|---|---|
| 2.1327 | 0.3175 | 200 | 2.5506 | 0.5249 | 0.55 | 0.5030 |
| 2.1102 | 0.6349 | 400 | 2.4539 | 0.5591 | 0.64 | 0.4819 |
| 1.9222 | 0.9524 | 600 | 2.4261 | 0.5838 | 0.49 | 0.5799 |
| 1.9188 | 1.2698 | 800 | 2.3813 | 0.5926 | 0.56 | 0.5731 |
| 1.8018 | 1.5873 | 1000 | 2.3515 | 0.6039 | 0.48 | 0.6000 |
| 1.8689 | 1.9048 | 1200 | 2.4095 | 0.6128 | 0.62 | 0.5877 |
| 1.6143 | 2.2222 | 1400 | 2.4082 | 0.6255 | 0.39 | 0.6155 |
| 1.5608 | 2.5397 | 1600 | 2.4122 | 0.6268 | 0.4600 | 0.6208 |
| 1.5566 | 2.8571 | 1800 | 2.3534 | 0.6396 | 0.33 | 0.6087 |
| 1.2670 | 3.1746 | 2000 | 2.8534 | 0.6235 | 0.67 | 0.6147 |
| 1.2466 | 3.4921 | 2200 | 2.7229 | 0.6352 | 0.36 | 0.6266 |
| 1.2686 | 3.8095 | 2400 | 2.7327 | 0.6417 | 0.47 | 0.6378 |
| 1.0226 | 4.1270 | 2600 | 3.0532 | 0.6301 | 0.5 | 0.6301 |
| 1.0627 | 4.4444 | 2800 | 3.1864 | 0.6326 | 0.66 | 0.6253 |
| 1.0418 | 4.7619 | 3000 | 3.1652 | 0.6345 | 0.5700 | 0.6295 |
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