End of training

README.md

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+---
+license: apache-2.0
+base_model: distilbert-base-uncased-finetuned-sst-2-english
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: distilbert-base-uncased-finetuned-sst2
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: sst2
+      split: validation
+      args: sst2
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9036697247706422
+---
+
+<!-- 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. -->
+
+# distilbert-base-uncased-finetuned-sst2
+
+This model is a fine-tuned version of [distilbert-base-uncased-finetuned-sst-2-english](https://huggingface.co/distilbert-base-uncased-finetuned-sst-2-english) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6600
+- Accuracy: 0.9037
+
+## 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: 5
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.0367        | 1.0   | 4210  | 0.5104          | 0.8968   |
+| 0.0287        | 2.0   | 8420  | 0.6466          | 0.9002   |
+| 0.0372        | 3.0   | 12630 | 0.5988          | 0.9014   |
+| 0.028         | 4.0   | 16840 | 0.6600          | 0.9037   |
+| 0.0111        | 5.0   | 21050 | 0.8030          | 0.9014   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 2.1.0+cu118
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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