update model card README.md

README.md

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+---
+license: mit
+tags:
+- text-classification
+- generated_from_trainer
+metrics:
+- accuracy
+- f1
+model-index:
+- name: deberta-v3-large-dapt-tapt-scientific-papers-pubmed-finetuned-DAGPap22
+  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-dapt-tapt-scientific-papers-pubmed-finetuned-DAGPap22
+
+This model is a fine-tuned version of [domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt](https://huggingface.co/domenicrosati/deberta-v3-large-dapt-scientific-papers-pubmed-tapt) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.0002
+- Accuracy: 0.9998
+- F1: 0.9999
+
+## 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: 12
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
+| 0.1884        | 1.0   | 669  | 0.0248          | 0.9951   | 0.9964 |
+| 0.0494        | 2.0   | 1338 | 0.0084          | 0.9987   | 0.9990 |
+| 0.0199        | 3.0   | 2007 | 0.0051          | 0.9991   | 0.9993 |
+| 0.0079        | 4.0   | 2676 | 0.0030          | 0.9993   | 0.9995 |
+| 0.0           | 5.0   | 3345 | 0.0026          | 0.9994   | 0.9996 |
+| 0.0           | 6.0   | 4014 | 0.0014          | 0.9996   | 0.9997 |
+| 0.0           | 7.0   | 4683 | 0.0015          | 0.9996   | 0.9997 |
+| 0.0           | 8.0   | 5352 | 0.0011          | 0.9996   | 0.9997 |
+| 0.0143        | 9.0   | 6021 | 0.0000          | 1.0      | 1.0    |
+| 0.0           | 10.0  | 6690 | 0.0035          | 0.9991   | 0.9993 |
+| 0.0           | 11.0  | 7359 | 0.0004          | 0.9998   | 0.9999 |
+| 0.0           | 12.0  | 8028 | 0.0002          | 0.9998   | 0.9999 |
+
+
+### Framework versions
+
+- Transformers 4.18.0
+- Pytorch 1.11.0
+- Datasets 2.1.0
+- Tokenizers 0.12.1