End of training

README.md

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+---
+license: apache-2.0
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: bert-tiny-emotion-KD-distilBERT
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: default
+      split: train
+      args: default
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.913
+---
+
+<!-- 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-tiny-emotion-KD-distilBERT
+
+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 emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5444
+- Accuracy: 0.913
+
+## 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: 50
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch | Step  | Validation Loss | Accuracy |
+|:-------------:|:-----:|:-----:|:---------------:|:--------:|
+| 4.2533        | 1.0   | 1000  | 2.8358          | 0.7675   |
+| 2.3274        | 2.0   | 2000  | 1.5893          | 0.8675   |
+| 1.3974        | 3.0   | 3000  | 1.0286          | 0.891    |
+| 0.9035        | 4.0   | 4000  | 0.7534          | 0.8955   |
+| 0.6619        | 5.0   | 5000  | 0.6350          | 0.905    |
+| 0.5482        | 6.0   | 6000  | 0.6180          | 0.899    |
+| 0.4937        | 7.0   | 7000  | 0.5448          | 0.91     |
+| 0.4013        | 8.0   | 8000  | 0.5493          | 0.906    |
+| 0.3839        | 9.0   | 9000  | 0.5481          | 0.9095   |
+| 0.3281        | 10.0  | 10000 | 0.5528          | 0.9115   |
+| 0.3098        | 11.0  | 11000 | 0.5864          | 0.9095   |
+| 0.2762        | 12.0  | 12000 | 0.5566          | 0.9095   |
+| 0.2467        | 13.0  | 13000 | 0.5444          | 0.913    |
+| 0.2286        | 14.0  | 14000 | 0.5306          | 0.912    |
+| 0.2215        | 15.0  | 15000 | 0.5312          | 0.9115   |
+| 0.2038        | 16.0  | 16000 | 0.5242          | 0.912    |
+
+
+### Framework versions
+
+- Transformers 4.22.1
+- Pytorch 1.12.1+cu113
+- Datasets 2.5.1
+- Tokenizers 0.12.1

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