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test_trainer
gyesibiney/test_trainer
test_trainer is a text classification model from gyesibiney. Use it when you need a label for a piece of text. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- Model type
- roberta
- Access
- Public
- Created
- Sep 8, 2023
- Updated
- Sep 8, 2023
- SHA
- 737c3666
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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. -->
test_trainer
This model is a fine-tuned version of gyesibiney/covid-tweet-sentimental-Analysis-roberta on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5256
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
- 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 |
|---|---|---|---|
| 0.6341 | 0.2 | 500 | 0.6156 |
| 0.5846 | 0.4 | 1000 | 0.6548 |
| 0.5447 | 0.6 | 1500 | 0.5651 |
| 0.523 | 0.8 | 2000 | 0.4769 |
| 0.5087 | 1.0 | 2500 | 0.4937 |
| 0.4791 | 1.2 | 3000 | 0.4567 |
| 0.4681 | 1.41 | 3500 | 0.4609 |
| 0.4255 | 1.61 | 4000 | 0.5214 |
| 0.4474 | 1.81 | 4500 | 0.5182 |
| 0.4271 | 2.01 | 5000 | 0.4983 |
| 0.4008 | 2.21 | 5500 | 0.4944 |
| 0.384 | 2.41 | 6000 | 0.4585 |
| 0.3629 | 2.61 | 6500 | 0.5462 |
| 0.3695 | 2.81 | 7000 | 0.5256 |
Framework versions
- Transformers 4.33.1
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- roberta
- Created
- Sep 8, 2023
- Updated
- Sep 8, 2023