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ABSA-SentencePair-DAPT-HARDAR-bert-base-Camel-MSA-ru3
salohnana2018/ABSA-SentencePair-DAPT-HARDAR-bert-base-Camel-MSA-ru3
ABSA-SentencePair-DAPT-HARDAR-bert-base-Camel-MSA-ru3 is a text classification model from salohnana2018. 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 3, 2024
- Updated
- Mar 3, 2024
- SHA
- 9031dafd
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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. -->
ABSA-SentencePair-DAPT-HARDAR-bert-base-Camel-MSA-ru3
This model is a fine-tuned version of salohnana2018/CAMEL-BERT-MSA-domianAdaption-Single-ABSA-HARD on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.1055
- Accuracy: 0.9026
- F1: 0.9026
- Precision: 0.9026
- Recall: 0.9026
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: 32
- eval_batch_size: 32
- seed: 23
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 20
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.0585 | 1.0 | 265 | 0.0424 | 0.8497 | 0.8497 | 0.8497 | 0.8497 |
| 0.0377 | 2.0 | 530 | 0.0422 | 0.8861 | 0.8861 | 0.8861 | 0.8861 |
| 0.0259 | 3.0 | 795 | 0.0421 | 0.8819 | 0.8819 | 0.8819 | 0.8819 |
| 0.017 | 4.0 | 1060 | 0.0477 | 0.8899 | 0.8899 | 0.8899 | 0.8899 |
| 0.0108 | 5.0 | 1325 | 0.0582 | 0.8927 | 0.8927 | 0.8927 | 0.8927 |
| 0.0085 | 6.0 | 1590 | 0.0650 | 0.8899 | 0.8899 | 0.8899 | 0.8899 |
| 0.0063 | 7.0 | 1855 | 0.0680 | 0.8922 | 0.8922 | 0.8922 | 0.8922 |
| 0.0043 | 8.0 | 2120 | 0.0705 | 0.9003 | 0.9003 | 0.9003 | 0.9003 |
| 0.0042 | 9.0 | 2385 | 0.0711 | 0.8974 | 0.8974 | 0.8974 | 0.8974 |
| 0.003 | 10.0 | 2650 | 0.0773 | 0.8979 | 0.8979 | 0.8979 | 0.8979 |
| 0.0026 | 11.0 | 2915 | 0.0842 | 0.8965 | 0.8965 | 0.8965 | 0.8965 |
| 0.002 | 12.0 | 3180 | 0.0888 | 0.8979 | 0.8979 | 0.8979 | 0.8979 |
| 0.002 | 13.0 | 3445 | 0.0896 | 0.8970 | 0.8970 | 0.8970 | 0.8970 |
| 0.0015 | 14.0 | 3710 | 0.0930 | 0.9008 | 0.9008 | 0.9008 | 0.9008 |
| 0.0012 | 15.0 | 3975 | 0.1008 | 0.9003 | 0.9003 | 0.9003 | 0.9003 |
| 0.0015 | 16.0 | 4240 | 0.0987 | 0.9017 | 0.9017 | 0.9017 | 0.9017 |
| 0.0011 | 17.0 | 4505 | 0.1030 | 0.9017 | 0.9017 | 0.9017 | 0.9017 |
| 0.0011 | 18.0 | 4770 | 0.1051 | 0.9003 | 0.9003 | 0.9003 | 0.9003 |
| 0.0011 | 19.0 | 5035 | 0.1046 | 0.9036 | 0.9036 | 0.9036 | 0.9036 |
| 0.001 | 20.0 | 5300 | 0.1055 | 0.9026 | 0.9026 | 0.9026 | 0.9026 |
Framework versions
- Transformers 4.38.1
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Mar 3, 2024
- Updated
- Mar 3, 2024