update model card README.md

README.md

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+---
+license: mit
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+- precision
+- recall
+- f1
+model-index:
+- name: mdeberta-profane-final
+  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. -->
+
+# mdeberta-profane-final
+
+This model is a fine-tuned version of [microsoft/mdeberta-v3-base](https://huggingface.co/microsoft/mdeberta-v3-base) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2269
+- Accuracy: 0.9154
+- Precision: 0.8684
+- Recall: 0.8558
+- F1: 0.8618
+
+## 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: 1e-05
+- train_batch_size: 32
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1     |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
+| No log        | 1.0   | 296  | 0.2324          | 0.9125   | 0.8672    | 0.8446 | 0.8552 |
+| 0.3129        | 2.0   | 592  | 0.2081          | 0.9202   | 0.8814    | 0.8549 | 0.8673 |
+| 0.3129        | 3.0   | 888  | 0.2155          | 0.9183   | 0.8747    | 0.8575 | 0.8657 |
+| 0.2136        | 4.0   | 1184 | 0.2164          | 0.9154   | 0.8738    | 0.8464 | 0.8591 |
+| 0.2136        | 5.0   | 1480 | 0.2269          | 0.9154   | 0.8684    | 0.8558 | 0.8618 |
+
+
+### Framework versions
+
+- Transformers 4.24.0.dev0
+- Pytorch 1.11.0+cu102
+- Datasets 2.6.1
+- Tokenizers 0.13.1