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update model card README.md
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README.md
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---
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license: mit
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tags:
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- generated_from_trainer
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metrics:
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- accuracy
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- precision
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- recall
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- f1
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model-index:
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- name: smalldata-microsoft-deberta-base-mnli-eng-only-sentiment-single-finetuned-memes
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# smalldata-microsoft-deberta-base-mnli-eng-only-sentiment-single-finetuned-memes
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This model is a fine-tuned version of [jayantapaul888/twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes](https://huggingface.co/jayantapaul888/twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.7400
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- Accuracy: 0.8816
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- Precision: 0.8946
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- Recall: 0.8937
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- F1: 0.8937
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 6
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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| No log | 1.0 | 378 | 0.2962 | 0.8764 | 0.8917 | 0.8881 | 0.8884 |
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| 0.3387 | 2.0 | 756 | 0.2803 | 0.8831 | 0.8950 | 0.8942 | 0.8946 |
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| 0.1693 | 3.0 | 1134 | 0.4289 | 0.8764 | 0.8912 | 0.8892 | 0.8886 |
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| 0.0772 | 4.0 | 1512 | 0.5436 | 0.8690 | 0.8822 | 0.8823 | 0.8822 |
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| 0.0772 | 5.0 | 1890 | 0.6566 | 0.8831 | 0.8960 | 0.8947 | 0.8949 |
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| 0.024 | 6.0 | 2268 | 0.7400 | 0.8816 | 0.8946 | 0.8937 | 0.8937 |
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### Framework versions
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- Transformers 4.24.0.dev0
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- Pytorch 1.11.0+cu102
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- Datasets 2.6.1
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- Tokenizers 0.13.1
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