Downloads · 30 days
4
18% of all-time downloads
roberta-large_MBTI_F_MBTI_agg_balanced_50_5e-06
DrinkIcedT/roberta-large_MBTI_F_MBTI_agg_balanced_50_5e-06
roberta-large_MBTI_F_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. --
All-time downloads
22
Public
Parameters
355M
1.4 GB on disk
Likes
0
Public
Repo makeup
Click a slice to open those files.
.safetensors1.4 GB · 100%
At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Aug 17, 2026
- Updated
- Aug 17, 2026
- SHA
- 92e9e07f
Try a prompt
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_5e-06
This model was trained from scratch on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 2.4601
- F1: 0.7494
- Threshold: 0.4
- F1 At 05: 0.7485
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 |
|---|---|---|---|---|---|---|
| 2.5767 | 0.3175 | 200 | 2.4598 | 0.6641 | 0.4 | 0.6454 |
| 2.2841 | 0.6349 | 400 | 2.3178 | 0.7037 | 0.4 | 0.6560 |
| 2.0780 | 0.9524 | 600 | 2.3261 | 0.7185 | 0.62 | 0.7027 |
| 1.9341 | 1.2698 | 800 | 2.0510 | 0.7444 | 0.4400 | 0.7375 |
| 1.7952 | 1.5873 | 1000 | 2.1067 | 0.7508 | 0.54 | 0.7489 |
| 1.7703 | 1.9048 | 1200 | 2.0659 | 0.7553 | 0.4600 | 0.7537 |
| 1.4937 | 2.2222 | 1400 | 2.1364 | 0.7542 | 0.47 | 0.7517 |
| 1.4845 | 2.5397 | 1600 | 2.2014 | 0.7558 | 0.54 | 0.7535 |
| 1.4268 | 2.8571 | 1800 | 2.1383 | 0.7560 | 0.49 | 0.7554 |
| 1.2178 | 3.1746 | 2000 | 2.3222 | 0.7492 | 0.47 | 0.7484 |
| 1.2976 | 3.4921 | 2200 | 2.2981 | 0.7503 | 0.54 | 0.7475 |
| 1.2173 | 3.8095 | 2400 | 2.3874 | 0.7471 | 0.47 | 0.7458 |
| 1.0743 | 4.1270 | 2600 | 2.4814 | 0.7502 | 0.53 | 0.7481 |
| 1.0434 | 4.4444 | 2800 | 2.4879 | 0.7464 | 0.5700 | 0.7442 |
| 1.0095 | 4.7619 | 3000 | 2.4601 | 0.7494 | 0.4 | 0.7485 |
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