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xnli_m_bert_only_hi
semindan/xnli_m_bert_only_hi
xnli_m_bert_only_hi is a text classification model from semindan. 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
- Nov 28, 2022
- Updated
- Jan 7, 2023
- SHA
- 220944a5
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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. -->
xnli_m_bert_only_hi
This model is a fine-tuned version of bert-base-multilingual-cased on the xnli dataset. It achieves the following results on the evaluation set:
- Loss: 1.5129
- Accuracy: 0.6458
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: 128
- eval_batch_size: 128
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.7554 | 1.0 | 3068 | 0.8254 | 0.6454 |
| 0.6896 | 2.0 | 6136 | 0.7786 | 0.6687 |
| 0.6214 | 3.0 | 9204 | 0.7973 | 0.6639 |
| 0.552 | 4.0 | 12272 | 0.7985 | 0.6751 |
| 0.4764 | 5.0 | 15340 | 0.9175 | 0.6759 |
| 0.4012 | 6.0 | 18408 | 1.0097 | 0.6558 |
| 0.329 | 7.0 | 21476 | 1.0889 | 0.6590 |
| 0.2646 | 8.0 | 24544 | 1.2490 | 0.6582 |
| 0.2157 | 9.0 | 27612 | 1.4154 | 0.6466 |
| 0.1761 | 10.0 | 30680 | 1.5129 | 0.6458 |
Framework versions
- Transformers 4.24.0
- Pytorch 1.13.0
- Datasets 2.6.1
- Tokenizers 0.13.1
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Nov 28, 2022
- Updated
- Jan 7, 2023