update model card README.md

README.md

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+---
+base_model: allenai/scibert_scivocab_uncased
+tags:
+- generated_from_trainer
+metrics:
+- accuracy
+model-index:
+- name: patentClassfication3
+  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. -->
+
+# patentClassfication3
+
+This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5828
+- Accuracy: 0.6901
+
+## 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: 2.51444e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 61
+- gradient_accumulation_steps: 8
+- total_train_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- lr_scheduler_warmup_steps: 240
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.6511        | 1.0   | 554  | 0.6841          | 0.6125   |
+| 0.5721        | 2.0   | 1108 | 0.5828          | 0.6901   |
+
+
+### Framework versions
+
+- Transformers 4.31.0
+- Pytorch 2.0.0
+- Datasets 2.14.4
+- Tokenizers 0.13.3