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my_distilbert_model
ggblake/my_distilbert_model
my_distilbert_model is a text classification model from ggblake. 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 23, 2023
- Updated
- Nov 23, 2023
- SHA
- bd2baa6c
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Base models
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. -->
my_distilbert_model
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: 0.5319
- Accuracy: 0.8537
- F1: 0.8537
- Precision: 0.8537
- Recall: 0.8537
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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.4318 | 1.0 | 534 | 0.3795 | 0.8415 | 0.8413 | 0.8425 | 0.8415 |
| 0.243 | 2.0 | 1068 | 0.4309 | 0.8490 | 0.8490 | 0.8490 | 0.8490 |
| 0.1669 | 3.0 | 1602 | 0.5319 | 0.8537 | 0.8537 | 0.8537 | 0.8537 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu118
- Datasets 2.15.0
- Tokenizers 0.15.0
- Task
- Text Classification
- Library
- transformers
- Type
- distilbert
- License
- apache-2.0
- Created
- Nov 23, 2023
- Updated
- Nov 23, 2023