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distilbert-base-uncased-finetuned-sst2
cvapict/distilbert-base-uncased-finetuned-sst2
distilbert-base-uncased-finetuned-sst2 is a machine learning model from cvapict. 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
- Sep 12, 2024
- Updated
- Sep 12, 2024
- SHA
- fc18d073
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. -->
distilbert-base-uncased-finetuned-sst2
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: 0.2481
- Accuracy: 0.9226
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 361 | 0.2881 | 0.9069 |
| 0.4544 | 2.0 | 722 | 0.2481 | 0.9226 |
| 0.1725 | 3.0 | 1083 | 0.2768 | 0.9169 |
| 0.1725 | 4.0 | 1444 | 0.2931 | 0.9183 |
| 0.0824 | 5.0 | 1805 | 0.2991 | 0.9226 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.1
- Datasets 2.15.0
- Tokenizers 0.15.0
- Type
- distilbert
- License
- apache-2.0
- Created
- Sep 12, 2024
- Updated
- Sep 12, 2024