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update model card 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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  # twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes
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- This model is a fine-tuned version of [microsoft/deberta-base-mnli](https://huggingface.co/microsoft/deberta-base-mnli) on the None dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 0.2523
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- - Accuracy: 0.9292
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- - Precision: 0.9300
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- - Recall: 0.9292
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- - F1: 0.9293
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 0.3522 | 1.0 | 1783 | 0.2881 | 0.9074 | 0.9080 | 0.9074 | 0.9071 |
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- | 0.2545 | 2.0 | 3566 | 0.2567 | 0.9221 | 0.9226 | 0.9221 | 0.9218 |
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- | 0.2205 | 3.0 | 5349 | 0.2411 | 0.9271 | 0.9288 | 0.9271 | 0.9273 |
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- | 0.1917 | 4.0 | 7132 | 0.2386 | 0.9296 | 0.9308 | 0.9296 | 0.9297 |
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- | 0.1755 | 5.0 | 8915 | 0.2499 | 0.9290 | 0.9295 | 0.9290 | 0.9289 |
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- | 0.1597 | 6.0 | 10698 | 0.2523 | 0.9292 | 0.9300 | 0.9292 | 0.9293 |
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  ### Framework versions
 
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  ---
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+ license: apache-2.0
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  tags:
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  - generated_from_trainer
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  metrics:
 
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  # twitter-data-microsoft-deberta-base-mnli-sentiment-finetuned-memes
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+ This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the None dataset.
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  It achieves the following results on the evaluation set:
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+ - Loss: 0.2466
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+ - Accuracy: 0.9296
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+ - Precision: 0.9308
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+ - Recall: 0.9296
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+ - F1: 0.9297
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  ## Model description
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:-----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 0.3533 | 1.0 | 1762 | 0.3078 | 0.9020 | 0.9037 | 0.9020 | 0.9020 |
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+ | 0.2664 | 2.0 | 3524 | 0.2622 | 0.9208 | 0.9219 | 0.9208 | 0.9207 |
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+ | 0.227 | 3.0 | 5286 | 0.2514 | 0.9253 | 0.9267 | 0.9253 | 0.9254 |
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+ | 0.2081 | 4.0 | 7048 | 0.2458 | 0.9268 | 0.9275 | 0.9268 | 0.9268 |
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+ | 0.187 | 5.0 | 8810 | 0.2450 | 0.9292 | 0.9300 | 0.9292 | 0.9292 |
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+ | 0.1802 | 6.0 | 10572 | 0.2466 | 0.9296 | 0.9308 | 0.9296 | 0.9297 |
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  ### Framework versions