End of training

README.md

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+---
+base_model: gokuls/bert_12_layer_model_v1_complete_training_new_48
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: hbertv1-massive-logit_KD_new
+  results:
+  - task:
+      name: Text Classification
+      type: text-classification
+    dataset:
+      name: massive
+      type: massive
+      config: en-US
+      split: validation
+      args: en-US
+    metrics:
+    - name: Accuracy
+      type: accuracy
+      value: 0.853910477127398
+---
+
+<!-- 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-massive-logit_KD_new
+
+This model is a fine-tuned version of [gokuls/bert_12_layer_model_v1_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v1_complete_training_new_48) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5587
+- Accuracy: 0.8539
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.3071        | 1.0   | 180  | 1.0522          | 0.7019   |
+| 0.9618        | 2.0   | 360  | 0.7397          | 0.7836   |
+| 0.6757        | 3.0   | 540  | 0.7535          | 0.7831   |
+| 0.5344        | 4.0   | 720  | 0.6076          | 0.8269   |
+| 0.4319        | 5.0   | 900  | 0.6585          | 0.8165   |
+| 0.3648        | 6.0   | 1080 | 0.5726          | 0.8362   |
+| 0.3326        | 7.0   | 1260 | 0.5642          | 0.8372   |
+| 0.2904        | 8.0   | 1440 | 0.5858          | 0.8352   |
+| 0.2554        | 9.0   | 1620 | 0.5521          | 0.8411   |
+| 0.2314        | 10.0  | 1800 | 0.5571          | 0.8436   |
+| 0.2192        | 11.0  | 1980 | 0.5479          | 0.8470   |
+| 0.2           | 12.0  | 2160 | 0.5587          | 0.8539   |
+| 0.1924        | 13.0  | 2340 | 0.5430          | 0.8480   |
+| 0.1683        | 14.0  | 2520 | 0.5647          | 0.8490   |
+| 0.1703        | 15.0  | 2700 | 0.5467          | 0.8515   |
+| 0.1598        | 16.0  | 2880 | 0.5578          | 0.8510   |
+| 0.1522        | 17.0  | 3060 | 0.5682          | 0.8431   |
+
+
+### Framework versions
+
+- Transformers 4.35.2
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.15.0
+- Tokenizers 0.15.0

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