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Sentiment-classfication-distilBERT-model
aaronayitey/Sentiment-classfication-distilBERT-model
Sentiment-classfication-distilBERT-model is a text classification model from aaronayitey. 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
- bert
- Access
- Public
- Created
- Nov 11, 2023
- Updated
- Nov 11, 2023
- SHA
- b717df90
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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. -->
Sentiment-classfication-distilBERT-model
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3217
- Accuracy: 0.9301
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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 1.11 | 0.14 | 100 | 1.0458 | 0.4603 |
| 0.9647 | 0.27 | 200 | 0.9241 | 0.5743 |
| 0.8498 | 0.41 | 300 | 0.7957 | 0.6365 |
| 0.7436 | 0.54 | 400 | 0.7044 | 0.7043 |
| 0.683 | 0.68 | 500 | 0.7109 | 0.7040 |
| 0.6407 | 0.81 | 600 | 0.5602 | 0.7872 |
| 0.5388 | 0.95 | 700 | 0.5073 | 0.8031 |
| 0.449 | 1.09 | 800 | 0.4736 | 0.8316 |
| 0.4136 | 1.22 | 900 | 0.5387 | 0.8147 |
| 0.3329 | 1.36 | 1000 | 0.4277 | 0.8615 |
| 0.3405 | 1.49 | 1100 | 0.3667 | 0.8730 |
| 0.2806 | 1.63 | 1200 | 0.3420 | 0.8832 |
| 0.2648 | 1.77 | 1300 | 0.3437 | 0.8975 |
| 0.2912 | 1.9 | 1400 | 0.3503 | 0.8914 |
| 0.2109 | 2.04 | 1500 | 0.3268 | 0.9182 |
| 0.1267 | 2.17 | 1600 | 0.3676 | 0.9182 |
| 0.0931 | 2.31 | 1700 | 0.3635 | 0.9250 |
| 0.1447 | 2.44 | 1800 | 0.3144 | 0.9233 |
| 0.0979 | 2.58 | 1900 | 0.3197 | 0.9301 |
| 0.1156 | 2.72 | 2000 | 0.3217 | 0.9301 |
| 0.0922 | 2.85 | 2100 | 0.3323 | 0.9294 |
| 0.1094 | 2.99 | 2200 | 0.2976 | 0.9304 |
| 0.0667 | 3.12 | 2300 | 0.3554 | 0.9318 |
| 0.0479 | 3.26 | 2400 | 0.3648 | 0.9318 |
| 0.0427 | 3.39 | 2500 | 0.3615 | 0.9331 |
| 0.0499 | 3.53 | 2600 | 0.3251 | 0.9389 |
| 0.0381 | 3.67 | 2700 | 0.3391 | 0.9362 |
| 0.0498 | 3.8 | 2800 | 0.3350 | 0.9365 |
| 0.0565 | 3.94 | 2900 | 0.3331 | 0.9375 |
Framework versions
- Transformers 4.35.0
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 11, 2023
- Updated
- Nov 11, 2023