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my_awesome_model
dshin/my_awesome_model
my_awesome_model is a text classification model from dshin. 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
- Mar 1, 2023
- Updated
- Mar 5, 2023
- SHA
- 419cf440
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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. -->
my_awesome_model
This model is a fine-tuned version of bert-base-uncased on the mic dataset. It achieves the following results on the evaluation set:
- Loss: 1.0634
- Accuracy: 0.6855
- F1: 0.6010
- Precision: 0.6053
- Recall: 0.5974
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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.7221 | 1.0 | 5689 | 0.7082 | 0.6943 | 0.5470 | 0.6322 | 0.5336 |
| 0.6334 | 2.0 | 11378 | 0.7100 | 0.7048 | 0.5810 | 0.6452 | 0.5573 |
| 0.5185 | 3.0 | 17067 | 0.7709 | 0.6968 | 0.6057 | 0.6162 | 0.6001 |
| 0.3962 | 4.0 | 22756 | 0.8961 | 0.6881 | 0.6050 | 0.6091 | 0.6014 |
| 0.2962 | 5.0 | 28445 | 1.0634 | 0.6855 | 0.6010 | 0.6053 | 0.5974 |
Framework versions
- Transformers 4.26.1
- Pytorch 1.13.1
- Datasets 2.10.0
- Tokenizers 0.12.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 1, 2023
- Updated
- Mar 5, 2023