Model save

README.md

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+---
+license: apache-2.0
+base_model: bert-base-uncased
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: bert-base-uncased-finetuned-CLS-RTE
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: rte
+      split: validation
+      args: rte
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.6967509025270758
+---
+
+<!-- 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. -->
+
+# bert-base-uncased-finetuned-CLS-RTE
+
+This model is a fine-tuned version of [bert-base-uncased](https://huggingface.co/bert-base-uncased) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2843
+- Accuracy: 0.6968
+
+## 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: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| No log        | 1.0   | 156  | 0.6285          | 0.6390   |
+| No log        | 2.0   | 312  | 0.6483          | 0.6679   |
+| No log        | 3.0   | 468  | 0.8430          | 0.7004   |
+| 0.4504        | 4.0   | 624  | 1.2886          | 0.6606   |
+| 0.4504        | 5.0   | 780  | 1.6445          | 0.7004   |
+| 0.4504        | 6.0   | 936  | 1.8099          | 0.6751   |
+| 0.0631        | 7.0   | 1092 | 1.8173          | 0.7040   |
+| 0.0631        | 8.0   | 1248 | 1.9799          | 0.7004   |
+| 0.0631        | 9.0   | 1404 | 1.9767          | 0.6968   |
+| 0.0159        | 10.0  | 1560 | 2.1696          | 0.6715   |
+| 0.0159        | 11.0  | 1716 | 2.2142          | 0.6859   |
+| 0.0159        | 12.0  | 1872 | 2.2605          | 0.6823   |
+| 0.0076        | 13.0  | 2028 | 2.2775          | 0.7040   |
+| 0.0076        | 14.0  | 2184 | 2.2719          | 0.6968   |
+| 0.0076        | 15.0  | 2340 | 2.2843          | 0.6968   |
+
+
+### Framework versions
+
+- Transformers 4.36.1
+- Pytorch 2.1.2
+- Datasets 2.15.0
+- Tokenizers 0.15.0

model.safetensors

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