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mini_text_classification_finetune_model
mankra/mini_text_classification_finetune_model
mini_text_classification_finetune_model is a text classification model from mankra. 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
- xlm-roberta
- Access
- Public
- Created
- Jul 7, 2023
- Updated
- Jul 7, 2023
- SHA
- b4a08f09
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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. -->
mini_text_classification_finetune_model
This model is a fine-tuned version of microsoft/Multilingual-MiniLM-L12-H384 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2095
- Accuracy: 0.3333
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: 30
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| No log | 1.0 | 1 | 1.3045 | 0.3333 |
| No log | 2.0 | 2 | 1.2998 | 0.3333 |
| No log | 3.0 | 3 | 1.2947 | 0.3333 |
| No log | 4.0 | 4 | 1.2899 | 0.3333 |
| No log | 5.0 | 5 | 1.2851 | 0.3333 |
| No log | 6.0 | 6 | 1.2809 | 0.3333 |
| No log | 7.0 | 7 | 1.2766 | 0.3333 |
| No log | 8.0 | 8 | 1.2721 | 0.3333 |
| No log | 9.0 | 9 | 1.2684 | 0.3333 |
| No log | 10.0 | 10 | 1.2645 | 0.3333 |
| No log | 11.0 | 11 | 1.2607 | 0.3333 |
| No log | 12.0 | 12 | 1.2567 | 0.3333 |
| No log | 13.0 | 13 | 1.2528 | 0.3333 |
| No log | 14.0 | 14 | 1.2490 | 0.3333 |
| No log | 15.0 | 15 | 1.2451 | 0.3333 |
| No log | 16.0 | 16 | 1.2413 | 0.3333 |
| No log | 17.0 | 17 | 1.2377 | 0.3333 |
| No log | 18.0 | 18 | 1.2342 | 0.3333 |
| No log | 19.0 | 19 | 1.2307 | 0.3333 |
| No log | 20.0 | 20 | 1.2275 | 0.3333 |
| No log | 21.0 | 21 | 1.2244 | 0.3333 |
| No log | 22.0 | 22 | 1.2215 | 0.3333 |
| No log | 23.0 | 23 | 1.2190 | 0.3333 |
| No log | 24.0 | 24 | 1.2167 | 0.3333 |
| No log | 25.0 | 25 | 1.2147 | 0.3333 |
| No log | 26.0 | 26 | 1.2130 | 0.3333 |
| No log | 27.0 | 27 | 1.2116 | 0.3333 |
| No log | 28.0 | 28 | 1.2105 | 0.3333 |
| No log | 29.0 | 29 | 1.2098 | 0.3333 |
| No log | 30.0 | 30 | 1.2095 | 0.3333 |
Framework versions
- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- xlm-roberta
- License
- mit
- Created
- Jul 7, 2023
- Updated
- Jul 7, 2023