End of training

README.md

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+---
+license: apache-2.0
+base_model: google/bert_uncased_L-2_H-128_A-2
+tags:
+- generated_from_trainer
+datasets:
+- massive
+metrics:
+- accuracy
+model-index:
+- name: bert_uncased_L-2_H-128_A-2_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: 0.6733890801770782
+---
+
+<!-- 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-2_H-128_A-2_massive
+
+This model is a fine-tuned version of [google/bert_uncased_L-2_H-128_A-2](https://huggingface.co/google/bert_uncased_L-2_H-128_A-2) on the massive dataset.
+It achieves the following results on the evaluation set:
+- Loss: 1.6807
+- Accuracy: 0.6734
+
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|
+| 3.8812        | 1.0   | 180  | 3.6329          | 0.2086   |
+| 3.4819        | 2.0   | 360  | 3.2331          | 0.3074   |
+| 3.1331        | 3.0   | 540  | 2.9025          | 0.3847   |
+| 2.8406        | 4.0   | 720  | 2.6372          | 0.4624   |
+| 2.6013        | 5.0   | 900  | 2.4211          | 0.5194   |
+| 2.4097        | 6.0   | 1080 | 2.2485          | 0.5539   |
+| 2.2504        | 7.0   | 1260 | 2.1084          | 0.5898   |
+| 2.1234        | 8.0   | 1440 | 1.9968          | 0.6085   |
+| 2.0195        | 9.0   | 1620 | 1.9036          | 0.6316   |
+| 1.9345        | 10.0  | 1800 | 1.8336          | 0.6463   |
+| 1.8616        | 11.0  | 1980 | 1.7722          | 0.6596   |
+| 1.8091        | 12.0  | 2160 | 1.7281          | 0.6645   |
+| 1.7704        | 13.0  | 2340 | 1.6984          | 0.6685   |
+| 1.7431        | 14.0  | 2520 | 1.6807          | 0.6734   |
+| 1.7293        | 15.0  | 2700 | 1.6749          | 0.6729   |
+
+
+### Framework versions
+
+- Transformers 4.34.0
+- Pytorch 1.14.0a0+410ce96
+- Datasets 2.14.5
+- Tokenizers 0.14.1

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