End of training

README.md

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+---
+base_model: gokuls/HBERTv1_48_L6_H768_A12
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: HBERTv1_48_L6_H768_A12_massive
+  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: 0.8627643876045253
+---
+
+<!-- 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_48_L6_H768_A12_massive
+
+This model is a fine-tuned version of [gokuls/HBERTv1_48_L6_H768_A12](https://huggingface.co/gokuls/HBERTv1_48_L6_H768_A12) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8228
+- Accuracy: 0.8628
+
+## 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: 15
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 1.8011        | 1.0   | 180  | 0.8508          | 0.7678   |
+| 0.712         | 2.0   | 360  | 0.7073          | 0.8121   |
+| 0.463         | 3.0   | 540  | 0.6127          | 0.8426   |
+| 0.3124        | 4.0   | 720  | 0.6141          | 0.8416   |
+| 0.2196        | 5.0   | 900  | 0.6738          | 0.8431   |
+| 0.1592        | 6.0   | 1080 | 0.7337          | 0.8387   |
+| 0.1209        | 7.0   | 1260 | 0.7453          | 0.8411   |
+| 0.0803        | 8.0   | 1440 | 0.7655          | 0.8460   |
+| 0.0552        | 9.0   | 1620 | 0.7871          | 0.8495   |
+| 0.0452        | 10.0  | 1800 | 0.7842          | 0.8598   |
+| 0.027         | 11.0  | 1980 | 0.8228          | 0.8628   |
+| 0.0149        | 12.0  | 2160 | 0.8452          | 0.8564   |
+| 0.0085        | 13.0  | 2340 | 0.8708          | 0.8554   |
+| 0.0052        | 14.0  | 2520 | 0.8564          | 0.8623   |
+| 0.0033        | 15.0  | 2700 | 0.8652          | 0.8588   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.14.5
+- Tokenizers 0.14.0

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