update model card README.md

README.md

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+---
+tags:
+- text-classification
+- generated_from_trainer
+metrics:
+- f1
+- precision
+- recall
+model-index:
+- name: deberta-v3-large-finetuned-dagpap22-only-and-real
+  results: []
+---
+
+<!-- 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. -->
+
+# deberta-v3-large-finetuned-dagpap22-only-and-real
+
+This model is a fine-tuned version of [domenicrosati/deberta-v3-large-finetuned-dagpap22-only-and-real](https://huggingface.co/domenicrosati/deberta-v3-large-finetuned-dagpap22-only-and-real) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0008
+- F1: 0.9999
+- Precision: 1.0
+- Recall: 0.9997
+
+## 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: 6e-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 50
+- num_epochs: 2
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | F1     | Precision | Recall |
+|:-------------:|:-----:|:-----:|:---------------:|:------:|:---------:|:------:|
+| 0.0016        | 1.0   | 10567 | 0.0060          | 0.9982 | 0.9997    | 0.9967 |
+| 0.0           | 2.0   | 21134 | 0.0008          | 0.9999 | 1.0       | 0.9997 |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1