End of training

README.md

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+---
+base_model: allenai/scibert_scivocab_uncased
+tags:
+- generated_from_trainer
+datasets:
+- scicite
+metrics:
+- accuracy
+model-index:
+- name: cite_classification
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: scicite
+      type: scicite
+      config: default
+      split: validation
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9170305676855895
+---
+
+<!-- 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. -->
+
+# cite_classification
+
+This model is a fine-tuned version of [allenai/scibert_scivocab_uncased](https://huggingface.co/allenai/scibert_scivocab_uncased) on the scicite dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6533
+- Accuracy: 0.9170
+
+## 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: 2e-05
+- train_batch_size: 16
+- eval_batch_size: 16
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 8
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 0.4909        | 1.0   | 719  | 0.2266          | 0.9181   |
+| 0.3215        | 2.0   | 1438 | 0.3707          | 0.9181   |
+| 0.0825        | 3.0   | 2157 | 0.5539          | 0.9159   |
+| 0.0539        | 4.0   | 2876 | 0.5117          | 0.9159   |
+| 0.0245        | 5.0   | 3595 | 0.5720          | 0.9094   |
+| 0.0209        | 6.0   | 4314 | 0.5710          | 0.9170   |
+| 0.0104        | 7.0   | 5033 | 0.6443          | 0.9116   |
+| 0.0059        | 8.0   | 5752 | 0.6533          | 0.9170   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 2.0.1+cu118
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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