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bart-large-mnli-Kaggle-Science-LLM-finetuned
satyanshu404/bart-large-mnli-Kaggle-Science-LLM-finetuned
bart-large-mnli-Kaggle-Science-LLM-finetuned is a text classification model from satyanshu404. 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
- bart
- Access
- Public
- Created
- Oct 3, 2023
- Updated
- Oct 3, 2023
- SHA
- 2b2b5767
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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. -->
bart-large-mnli-Kaggle-Science-LLM-finetuned
This model is a fine-tuned version of facebook/bart-large-mnli on the None dataset. It achieves the following results on the evaluation set:
- Loss: 2.7109
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: 2e-05
- train_batch_size: 1
- eval_batch_size: 1
- 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 |
|---|---|---|---|
| 0.7865 | 1.0 | 800 | 1.1187 |
| 0.6785 | 2.0 | 1600 | 1.2005 |
| 0.774 | 3.0 | 2400 | 1.1685 |
| 0.4621 | 4.0 | 3200 | 1.3130 |
| 0.4138 | 5.0 | 4000 | 2.2119 |
| 0.3162 | 6.0 | 4800 | 2.0261 |
| 0.2778 | 7.0 | 5600 | 1.9403 |
| 0.2476 | 8.0 | 6400 | 2.5232 |
| 0.1718 | 9.0 | 7200 | 2.6737 |
| 0.0869 | 10.0 | 8000 | 2.7109 |
Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
- Task
- Text Classification
- Library
- transformers
- Type
- bart
- License
- mit
- Created
- Oct 3, 2023
- Updated
- Oct 3, 2023