End of training

README.md

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+---
+base_model: gokuls/model_v1_complete_training_wt_init_48_small_freeze_new
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: hbertv1-emotion-logit_KD-small
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: emotion
+      type: emotion
+      config: split
+      split: validation
+      args: split
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.9335
+---
+
+<!-- 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. -->
+
+# hbertv1-emotion-logit_KD-small
+
+This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_small_freeze_new](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_small_freeze_new) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.2473
+- Accuracy: 0.9335
+
+## 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: 64
+- eval_batch_size: 64
+- seed: 33
+- distributed_type: multi-GPU
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 50
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.4023        | 1.0   | 250  | 0.5204          | 0.8825   |
+| 0.3903        | 2.0   | 500  | 0.3014          | 0.91     |
+| 0.2438        | 3.0   | 750  | 0.2849          | 0.9185   |
+| 0.1778        | 4.0   | 1000 | 0.2489          | 0.9265   |
+| 0.1394        | 5.0   | 1250 | 0.2878          | 0.9205   |
+| 0.1218        | 6.0   | 1500 | 0.2887          | 0.923    |
+| 0.1083        | 7.0   | 1750 | 0.2788          | 0.9285   |
+| 0.1019        | 8.0   | 2000 | 0.2373          | 0.928    |
+| 0.0898        | 9.0   | 2250 | 0.2473          | 0.9335   |
+| 0.0817        | 10.0  | 2500 | 0.2822          | 0.926    |
+| 0.0827        | 11.0  | 2750 | 0.2474          | 0.926    |
+| 0.0733        | 12.0  | 3000 | 0.2329          | 0.9285   |
+| 0.0631        | 13.0  | 3250 | 0.2301          | 0.929    |
+| 0.06          | 14.0  | 3500 | 0.2565          | 0.9295   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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