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distilbert-base-uncased_rotten_tomatoes
xianzhew/distilbert-base-uncased_rotten_tomatoes
distilbert-base-uncased_rotten_tomatoes is a text classification model from xianzhew. Use it when you need a label for a piece of text. It is set up for transformers. 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
- Task
- Text Classification
- Library
- transformers
- License
- apache-2.0
- Model type
- distilbert
- Access
- Public
- Created
- Nov 21, 2022
- Updated
- Nov 21, 2022
- SHA
- 3cdce7e8
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Datasets
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_rotten_tomatoes
This model is a fine-tuned version of distilbert-base-uncased on the rotten_tomatoes dataset. It achieves the following results on the evaluation set:
- Loss: 0.9770
- Accuracy: 0.8405
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-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 |
|---|---|---|---|---|
| 0.4274 | 1.0 | 534 | 0.3831 | 0.8452 |
| 0.2256 | 2.0 | 1068 | 0.5080 | 0.8405 |
| 0.1048 | 3.0 | 1602 | 0.7442 | 0.8368 |
| 0.0503 | 4.0 | 2136 | 0.8985 | 0.8443 |
| 0.0187 | 5.0 | 2670 | 0.9770 | 0.8405 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.12.1+cu113
- Datasets 2.7.0
- Tokenizers 0.13.2
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 21, 2022
- Updated
- Nov 21, 2022