End of training

README.md

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+---
+base_model: gokuls/HBERTv1_48_L4_H256_A4
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: HBERTv1_48_L4_H256_A4_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: 0.8401377274963109
+---
+
+<!-- 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_L4_H256_A4_massive
+
+This model is a fine-tuned version of [gokuls/HBERTv1_48_L4_H256_A4](https://huggingface.co/gokuls/HBERTv1_48_L4_H256_A4) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7151
+- Accuracy: 0.8401
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 3.206         | 1.0   | 180  | 2.2341          | 0.4579   |
+| 1.8169        | 2.0   | 360  | 1.3642          | 0.6749   |
+| 1.1697        | 3.0   | 540  | 1.0289          | 0.7423   |
+| 0.8587        | 4.0   | 720  | 0.8583          | 0.7821   |
+| 0.6723        | 5.0   | 900  | 0.8038          | 0.8008   |
+| 0.5497        | 6.0   | 1080 | 0.7459          | 0.8101   |
+| 0.4755        | 7.0   | 1260 | 0.7419          | 0.8146   |
+| 0.3992        | 8.0   | 1440 | 0.7095          | 0.8278   |
+| 0.336         | 9.0   | 1620 | 0.7278          | 0.8288   |
+| 0.2956        | 10.0  | 1800 | 0.7151          | 0.8401   |
+| 0.2593        | 11.0  | 1980 | 0.7130          | 0.8347   |
+| 0.2301        | 12.0  | 2160 | 0.7215          | 0.8367   |
+| 0.2038        | 13.0  | 2340 | 0.7191          | 0.8372   |
+| 0.1881        | 14.0  | 2520 | 0.7273          | 0.8362   |
+| 0.1766        | 15.0  | 2700 | 0.7256          | 0.8401   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.14.5
+- Tokenizers 0.14.0

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