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nli-finetune-model
underfit/nli-finetune-model
nli-finetune-model is a text classification model from underfit. 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
- Jun 12, 2023
- Updated
- Jun 15, 2023
- SHA
- f693eb71
Try a prompt
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. -->
nli-finetune-model
This model is a fine-tuned version of bert-large-uncased on the multi_nli dataset. It achieves the following results on the evaluation set:
- Loss: 1.2551
- Accuracy: 0.7793
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: 1e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.99) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 1
- num_epochs: 3.0
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|---|---|---|---|---|
| 0.6813 | 1.0 | 2500 | 0.6655 | 0.7657 |
| 0.5632 | 2.0 | 5000 | 1.0409 | 0.778 |
| 0.3753 | 3.0 | 7500 | 1.2551 | 0.7793 |
Framework versions
- Transformers 4.28.0
- Pytorch 1.13.1+cu117
- Datasets 2.12.0
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bert
- License
- apache-2.0
- Created
- Jun 12, 2023
- Updated
- Jun 15, 2023