End of training

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- glue
+metrics:
+- accuracy
+model-index:
+- name: tiny-bert-sst2-1_mobilebert-only-distillation
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: glue
+      type: glue
+      config: sst2
+      split: train
+      args: sst2
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.8291284403669725
+---
+
+<!-- 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. -->
+
+# tiny-bert-sst2-1_mobilebert-only-distillation
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the glue dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.2808
+- Accuracy: 0.8291
+
+## 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: 16
+- eval_batch_size: 16
+- seed: 33
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 0.4252        | 1.0   | 4210  | 2.6253          | 0.8142   |
+| 0.519         | 2.0   | 8420  | 2.4860          | 0.8245   |
+| 0.4986        | 3.0   | 12630 | 2.2808          | 0.8291   |
+| 0.4454        | 4.0   | 16840 | 2.5185          | 0.8280   |
+| 0.3912        | 5.0   | 21050 | 2.3982          | 0.8257   |
+| 0.3561        | 6.0   | 25260 | 2.4030          | 0.8211   |
+
+
+### Framework versions
+
+- Transformers 4.21.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.4.0
+- Tokenizers 0.12.1

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