End of training

README.md

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+---
+license: apache-2.0
+base_model: google/bert_uncased_L-6_H-768_A-12
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: bert_uncased_L-6_H-768_A-12_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: 0.8888342351205115
+---
+
+<!-- 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_uncased_L-6_H-768_A-12_massive
+
+This model is a fine-tuned version of [google/bert_uncased_L-6_H-768_A-12](https://huggingface.co/google/bert_uncased_L-6_H-768_A-12) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5459
+- Accuracy: 0.8888
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 2.0422        | 1.0   | 180  | 0.8433          | 0.8160   |
+| 0.6599        | 2.0   | 360  | 0.5532          | 0.8618   |
+| 0.3564        | 3.0   | 540  | 0.5180          | 0.8701   |
+| 0.212         | 4.0   | 720  | 0.4955          | 0.8805   |
+| 0.1358        | 5.0   | 900  | 0.5076          | 0.8844   |
+| 0.0859        | 6.0   | 1080 | 0.5193          | 0.8864   |
+| 0.059         | 7.0   | 1260 | 0.5459          | 0.8888   |
+| 0.038         | 8.0   | 1440 | 0.5811          | 0.8834   |
+| 0.0255        | 9.0   | 1620 | 0.5875          | 0.8849   |
+| 0.0171        | 10.0  | 1800 | 0.5881          | 0.8834   |
+| 0.0122        | 11.0  | 1980 | 0.6051          | 0.8829   |
+| 0.0086        | 12.0  | 2160 | 0.6117          | 0.8879   |
+| 0.007         | 13.0  | 2340 | 0.6032          | 0.8864   |
+| 0.006         | 14.0  | 2520 | 0.6112          | 0.8824   |
+| 0.0055        | 15.0  | 2700 | 0.6130          | 0.8844   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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