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my-dear-watson-nli-model
vempaliakhil/my-dear-watson-nli-model
my-dear-watson-nli-model is a text classification model from vempaliakhil. 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
- deberta-v2
- Access
- Public
- Created
- Apr 24, 2024
- Updated
- Apr 26, 2024
- SHA
- 8bf51d05
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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. -->
my-dear-watson-nli-model
This model is a fine-tuned version of MoritzLaurer/mDeBERTa-v3-base-xnli-multilingual-nli-2mil7 on the None dataset. It achieves the following results on the evaluation set:
- Loss: 1.1099
- Accuracy: 0.8309
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: 8e-05
- train_batch_size: 16
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 4
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.4693 | 1.0 | 682 | 0.5665 | 0.7921 |
| 0.3909 | 2.0 | 1364 | 0.5350 | 0.7995 |
| 0.1308 | 3.0 | 2046 | 0.7919 | 0.8325 |
| 0.0525 | 4.0 | 2728 | 1.1099 | 0.8309 |
Framework versions
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2
- Task
- Text Classification
- Library
- transformers
- Type
- deberta-v2
- License
- mit
- Created
- Apr 24, 2024
- Updated
- Apr 26, 2024