Training in progress, epoch 1

README.md

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+---
+base_model: gokuls/bert_12_layer_model_v3_complete_training_48
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: bert_12_layer_model_v3_48_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: 0.8598130841121495
+---
+
+<!-- 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. -->
+
+# bert_12_layer_model_v3_48_massive
+
+This model is a fine-tuned version of [gokuls/bert_12_layer_model_v3_complete_training_48](https://huggingface.co/gokuls/bert_12_layer_model_v3_complete_training_48) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8706
+- Accuracy: 0.8598
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.151         | 1.0   | 180  | 1.0701          | 0.7083   |
+| 0.9461        | 2.0   | 360  | 0.8522          | 0.7737   |
+| 0.6903        | 3.0   | 540  | 0.7244          | 0.8165   |
+| 0.5397        | 4.0   | 720  | 0.7617          | 0.8160   |
+| 0.4321        | 5.0   | 900  | 0.7426          | 0.8234   |
+| 0.3281        | 6.0   | 1080 | 0.7274          | 0.8392   |
+| 0.2678        | 7.0   | 1260 | 0.8035          | 0.8308   |
+| 0.2237        | 8.0   | 1440 | 0.7729          | 0.8431   |
+| 0.1689        | 9.0   | 1620 | 0.8122          | 0.8470   |
+| 0.1338        | 10.0  | 1800 | 0.8137          | 0.8455   |
+| 0.1002        | 11.0  | 1980 | 0.8369          | 0.8534   |
+| 0.0735        | 12.0  | 2160 | 0.8526          | 0.8554   |
+| 0.055         | 13.0  | 2340 | 0.8546          | 0.8554   |
+| 0.0362        | 14.0  | 2520 | 0.8706          | 0.8598   |
+| 0.0242        | 15.0  | 2700 | 0.8828          | 0.8598   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.14.5
+- Tokenizers 0.14.1

added_tokens.json

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+}

config.json

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+{
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+  "activation": "relu",
+  "architectures": [
+    "DistilBertForSequenceClassification"
+  ],
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+  "dim": 768,
+  "dropout": 0.05,
+  "hidden_dim": 3072,
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+  "model_type": "hybridbert",
+  "n_heads": 12,
+  "n_layers": 12,
+  "pad_token_id": 0,
+  "problem_type": "single_label_classification",
+  "qa_dropout": 0.1,
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+  "torch_dtype": "float32",
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+  "vocab_size": 30522
+}

pytorch_model.bin

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special_tokens_map.json

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tokenizer_config.json

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