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distilbert-base-uncased-finetuned-mrpc
centaur31/distilbert-base-uncased-finetuned-mrpc
distilbert-base-uncased-finetuned-mrpc is a machine learning model from centaur31. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as apache-2.0.
should probably proofread and complete it, then remove this comment. --
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At a glance
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 14, 2024
- Updated
- Nov 14, 2024
- SHA
- 7b9a550a
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. -->
distilbert-base-uncased-finetuned-mrpc
This model is a fine-tuned version of distilbert-base-uncased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3962
- Accuracy: 0.8382
- F1: 0.8893
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: 2e-05
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 1.0 | 230 | 0.4131 | 0.8186 | 0.875 |
| No log | 2.0 | 460 | 0.3962 | 0.8382 | 0.8893 |
Framework versions
- Transformers 4.28.0
- Pytorch 2.1.2+cu121
- Datasets 2.15.0
- Tokenizers 0.13.3
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 14, 2024
- Updated
- Nov 14, 2024