Model save

README.md

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+---
+license: apache-2.0
+base_model: kennethge123/superglue_rte-bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- bigbench
+metrics:
+- accuracy
+model-index:
+- name: entailed_after_rte-bert-base-uncased
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: bigbench
+      type: bigbench
+      config: entailed_polarity
+      split: validation
+      args: entailed_polarity
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.5714285714285714
+---
+
+<!-- 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. -->
+
+# entailed_after_rte-bert-base-uncased
+
+This model is a fine-tuned version of [kennethge123/superglue_rte-bert-base-uncased](https://huggingface.co/kennethge123/superglue_rte-bert-base-uncased) on the bigbench dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7322
+- Accuracy: 0.5714
+
+## 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: 5e-05
+- train_batch_size: 4
+- eval_batch_size: 32
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 20
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 30   | 0.6876          | 0.5714   |
+| No log        | 2.0   | 60   | 0.8029          | 0.5714   |
+| No log        | 3.0   | 90   | 0.7246          | 0.5714   |
+| No log        | 4.0   | 120  | 0.7152          | 0.5714   |
+| No log        | 5.0   | 150  | 0.7887          | 0.5714   |
+| No log        | 6.0   | 180  | 0.7498          | 0.5714   |
+| No log        | 7.0   | 210  | 0.8149          | 0.4286   |
+| No log        | 8.0   | 240  | 0.7055          | 0.5714   |
+| No log        | 9.0   | 270  | 0.7209          | 0.5714   |
+| No log        | 10.0  | 300  | 0.6922          | 0.5714   |
+| No log        | 11.0  | 330  | 0.7186          | 0.5714   |
+| No log        | 12.0  | 360  | 0.6916          | 0.5714   |
+| No log        | 13.0  | 390  | 0.7233          | 0.5714   |
+| No log        | 14.0  | 420  | 0.7109          | 0.5714   |
+| No log        | 15.0  | 450  | 0.7051          | 0.5714   |
+| No log        | 16.0  | 480  | 0.6968          | 0.5714   |
+| 0.7046        | 17.0  | 510  | 0.7068          | 0.5714   |
+| 0.7046        | 18.0  | 540  | 0.7319          | 0.5714   |
+| 0.7046        | 19.0  | 570  | 0.7301          | 0.5714   |
+| 0.7046        | 20.0  | 600  | 0.7322          | 0.5714   |
+
+
+### Framework versions
+
+- Transformers 4.37.0
+- Pytorch 1.13.1+cu117
+- Datasets 2.15.0
+- Tokenizers 0.15.2

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