End of training

README.md

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+---
+base_model: gokuls/model_v1_complete_training_wt_init_48_mini_freeze_new
+tags:
+- generated_from_trainer
+datasets:
+- emotion
+metrics:
+- accuracy
+model-index:
+- name: hbertv1-emotion-logit_KD-mini
+  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: 0.902
+---
+
+<!-- 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-mini
+
+This model is a fine-tuned version of [gokuls/model_v1_complete_training_wt_init_48_mini_freeze_new](https://huggingface.co/gokuls/model_v1_complete_training_wt_init_48_mini_freeze_new) on the emotion dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4302
+- Accuracy: 0.902
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.0557        | 1.0   | 250  | 0.9294          | 0.8275   |
+| 0.7977        | 2.0   | 500  | 0.5722          | 0.876    |
+| 0.531         | 3.0   | 750  | 0.5091          | 0.8805   |
+| 0.4472        | 4.0   | 1000 | 0.4683          | 0.8935   |
+| 0.39          | 5.0   | 1250 | 0.4489          | 0.8975   |
+| 0.3432        | 6.0   | 1500 | 0.4714          | 0.895    |
+| 0.3148        | 7.0   | 1750 | 0.4302          | 0.902    |
+| 0.2859        | 8.0   | 2000 | 0.4388          | 0.8955   |
+| 0.2635        | 9.0   | 2250 | 0.4317          | 0.9      |
+| 0.2409        | 10.0  | 2500 | 0.4433          | 0.901    |
+| 0.2249        | 11.0  | 2750 | 0.4413          | 0.89     |
+| 0.2159        | 12.0  | 3000 | 0.4607          | 0.897    |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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