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finetuned-Sentiment-classfication-BERT-model
Slygags/finetuned-Sentiment-classfication-BERT-model
finetuned-Sentiment-classfication-BERT-model is a text classification model from Slygags. 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
- May 2, 2023
- Updated
- May 6, 2023
- SHA
- a854462c
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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. -->
finetuned-Sentiment-classfication-BERT-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: 0.6050
- Rmse: 0.6736
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: 3e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 10
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Rmse |
|---|---|---|---|---|
| 0.7556 | 2.0 | 500 | 0.6050 | 0.6736 |
| 0.3957 | 4.0 | 1000 | 0.7329 | 0.6560 |
| 0.1413 | 6.0 | 1500 | 1.0727 | 0.6941 |
| 0.0598 | 8.0 | 2000 | 1.3042 | 0.6483 |
| 0.0319 | 10.0 | 2500 | 1.3687 | 0.6544 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- May 2, 2023
- Updated
- May 6, 2023