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distilroberta-fast-surgical
marcuscedricridia/distilroberta-fast-surgical
distilroberta-fast-surgical is a text classification model from marcuscedricridia. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- roberta
- Access
- Public
- Created
- Mar 2, 2026
- Updated
- Mar 3, 2026
- SHA
- e6db91d5
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Base models
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. -->
distilroberta-fast-surgical
This model is a fine-tuned version of noumenon-labs/Earlybird-fast on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0299
- Accuracy: 0.9876
- F1: 0.9876
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: 8e-06
- train_batch_size: 64
- eval_batch_size: 32
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED 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: 0.1
- num_epochs: 2
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0.1681 | 200 | 0.2195 | 0.8762 | 0.8746 |
| No log | 0.3361 | 400 | 0.0636 | 0.9704 | 0.9704 |
| 0.2821 | 0.5042 | 600 | 0.0600 | 0.9654 | 0.9653 |
| 0.2821 | 0.6723 | 800 | 0.0596 | 0.9655 | 0.9655 |
| 0.0404 | 0.8403 | 1000 | 0.1019 | 0.9456 | 0.9455 |
| 0.0404 | 1.0084 | 1200 | 0.0560 | 0.9734 | 0.9734 |
| 0.0404 | 1.1765 | 1400 | 0.0366 | 0.9842 | 0.9842 |
| 0.0253 | 1.3445 | 1600 | 0.0312 | 0.9875 | 0.9875 |
| 0.0253 | 1.5126 | 1800 | 0.0298 | 0.9878 | 0.9878 |
| 0.0201 | 1.6807 | 2000 | 0.0649 | 0.9682 | 0.9682 |
| 0.0201 | 1.8487 | 2200 | 0.0625 | 0.9697 | 0.9697 |
Framework versions
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.0.0
- Tokenizers 0.22.2
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- License
- mit
- Created
- Mar 2, 2026
- Updated
- Mar 3, 2026