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sexism-identification-coroseof
cosminc98/sexism-identification-coroseof
sexism-identification-coroseof is a text classification model from cosminc98. Use it when you need a label for a piece of text. It is set up for transformers. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Text Classification
- Library
- transformers
- License
- mit
- Model type
- bert
- Access
- Public
- Created
- Apr 16, 2023
- Updated
- Apr 18, 2023
- SHA
- 1c91793f
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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. -->
sexism-identification-coroseof
This model is a fine-tuned version of dumitrescustefan/bert-base-romanian-uncased-v1 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.6960
- Accuracy: 0.8499
- F1: 0.8537
- Balanced Accuracy: 0.6139
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: 0.0001
- train_batch_size: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 4
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Balanced Accuracy |
|---|---|---|---|---|---|---|
| No log | 1.0 | 488 | 0.9896 | 0.8125 | 0.8263 | 0.6059 |
| 0.9572 | 2.0 | 976 | 0.8694 | 0.7992 | 0.8202 | 0.7183 |
| 0.5835 | 3.0 | 1464 | 1.1954 | 0.8388 | 0.8477 | 0.6485 |
| 0.2833 | 4.0 | 1952 | 1.6960 | 0.8499 | 0.8537 | 0.6139 |
Framework versions
- Transformers 4.28.1
- Pytorch 2.0.0+cu117
- Datasets 2.11.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- mit
- Created
- Apr 16, 2023
- Updated
- Apr 18, 2023