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aunt_mai_ork_v2
BotnoiNLPteam/aunt_mai_ork_v2
aunt_mai_ork_v2 is a text classification model from BotnoiNLPteam. 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
- camembert
- Access
- Public
- Created
- Jul 25, 2024
- Updated
- Jul 25, 2024
- SHA
- 6eba739d
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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. -->
wisesight_sentiment
This model is a fine-tuned version of airesearch/wangchanberta-base-att-spm-uncased on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4140
- Accuracy: 0.9025
- F1 Micro: 0.9025
- Precision Micro: 0.9025
- Recall Micro: 0.9025
- F1 Macro: 0.9010
- Precision Macro: 0.9006
- Recall Macro: 0.9015
- Nb Samples: 1015
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: 4
- eval_batch_size: 4
- seed: 1412
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2031
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Micro | Precision Micro | Recall Micro | F1 Macro | Precision Macro | Recall Macro | Nb Samples |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.587 | 1.0 | 2031 | 0.5865 | 0.8532 | 0.8532 | 0.8532 | 0.8532 | 0.8492 | 0.8550 | 0.8460 | 1015 |
| 0.5212 | 2.0 | 4062 | 0.7026 | 0.8158 | 0.8158 | 0.8158 | 0.8158 | 0.8156 | 0.8380 | 0.8322 | 1015 |
| 0.4554 | 3.0 | 6093 | 0.4360 | 0.8768 | 0.8768 | 0.8768 | 0.8768 | 0.8731 | 0.8813 | 0.8690 | 1015 |
| 0.3752 | 4.0 | 8124 | 0.4121 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | 0.8867 | 0.8929 | 0.8831 | 1015 |
| 0.382 | 5.0 | 10155 | 0.4709 | 0.8916 | 0.8916 | 0.8916 | 0.8916 | 0.8894 | 0.8917 | 0.8876 | 1015 |
| 0.3465 | 6.0 | 12186 | 0.3929 | 0.8975 | 0.8975 | 0.8975 | 0.8975 | 0.8957 | 0.8964 | 0.8952 | 1015 |
| 0.3246 | 7.0 | 14217 | 0.4801 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | 0.8873 | 0.8899 | 0.8854 | 1015 |
| 0.2808 | 8.0 | 16248 | 0.5070 | 0.8897 | 0.8897 | 0.8897 | 0.8897 | 0.8881 | 0.8874 | 0.8889 | 1015 |
| 0.2786 | 9.0 | 18279 | 0.4098 | 0.8995 | 0.8995 | 0.8995 | 0.8995 | 0.8975 | 0.8993 | 0.8962 | 1015 |
| 0.2151 | 10.0 | 20310 | 0.4140 | 0.9025 | 0.9025 | 0.9025 | 0.9025 | 0.9010 | 0.9006 | 0.9015 | 1015 |
Framework versions
- Transformers 4.42.4
- Pytorch 2.3.1+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
- Task
- Text Classification
- Library
- transformers
- Type
- camembert
- Created
- Jul 25, 2024
- Updated
- Jul 25, 2024