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README.md
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---
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license: apache-2.0
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base_model: google/bert_uncased_L-10_H-128_A-2
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tags:
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- generated_from_trainer
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datasets:
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- massive
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metrics:
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- accuracy
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model-index:
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- name: bert_uncased_L-10_H-128_A-2_massive
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results:
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- task:
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name: Text Classification
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type: text-classification
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dataset:
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name: massive
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type: massive
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config: en-US
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split: validation
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args: en-US
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metrics:
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- name: Accuracy
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type: accuracy
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value: 0.7466797835710772
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# bert_uncased_L-10_H-128_A-2_massive
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This model is a fine-tuned version of [google/bert_uncased_L-10_H-128_A-2](https://huggingface.co/google/bert_uncased_L-10_H-128_A-2) on the massive dataset.
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It achieves the following results on the evaluation set:
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- Loss: 1.4064
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- Accuracy: 0.7467
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 5e-05
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- train_batch_size: 64
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- eval_batch_size: 64
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- seed: 33
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- distributed_type: multi-GPU
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 15
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:--------:|
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| 3.8032 | 1.0 | 180 | 3.4795 | 0.3296 |
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| 3.2716 | 2.0 | 360 | 2.9915 | 0.4491 |
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| 2.8593 | 3.0 | 540 | 2.6360 | 0.5145 |
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| 2.5442 | 4.0 | 720 | 2.3533 | 0.5765 |
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| 2.296 | 5.0 | 900 | 2.1403 | 0.6006 |
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| 2.0936 | 6.0 | 1080 | 1.9655 | 0.6463 |
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| 1.9277 | 7.0 | 1260 | 1.8291 | 0.6719 |
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| 1.7937 | 8.0 | 1440 | 1.7114 | 0.6911 |
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| 1.6829 | 9.0 | 1620 | 1.6267 | 0.7088 |
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| 1.5946 | 10.0 | 1800 | 1.5575 | 0.7231 |
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| 1.5258 | 11.0 | 1980 | 1.4976 | 0.7354 |
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| 1.4663 | 12.0 | 2160 | 1.4616 | 0.7364 |
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| 1.4256 | 13.0 | 2340 | 1.4296 | 0.7437 |
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| 1.3984 | 14.0 | 2520 | 1.4126 | 0.7442 |
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| 1.3824 | 15.0 | 2700 | 1.4064 | 0.7467 |
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### Framework versions
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- Transformers 4.34.0
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- Pytorch 1.14.0a0+410ce96
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- Datasets 2.14.5
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- Tokenizers 0.14.1
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