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--- |
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license: apache-2.0 |
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base_model: google/bert_uncased_L-2_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-2_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: 0.6733890801770782 |
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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-2_H-128_A-2_massive |
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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. |
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It achieves the following results on the evaluation set: |
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- Loss: 1.6807 |
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- Accuracy: 0.6734 |
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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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| 3.8812 | 1.0 | 180 | 3.6329 | 0.2086 | |
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| 3.4819 | 2.0 | 360 | 3.2331 | 0.3074 | |
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| 3.1331 | 3.0 | 540 | 2.9025 | 0.3847 | |
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| 2.8406 | 4.0 | 720 | 2.6372 | 0.4624 | |
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| 2.6013 | 5.0 | 900 | 2.4211 | 0.5194 | |
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| 2.4097 | 6.0 | 1080 | 2.2485 | 0.5539 | |
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| 2.2504 | 7.0 | 1260 | 2.1084 | 0.5898 | |
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| 2.1234 | 8.0 | 1440 | 1.9968 | 0.6085 | |
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| 2.0195 | 9.0 | 1620 | 1.9036 | 0.6316 | |
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| 1.9345 | 10.0 | 1800 | 1.8336 | 0.6463 | |
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| 1.8616 | 11.0 | 1980 | 1.7722 | 0.6596 | |
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| 1.8091 | 12.0 | 2160 | 1.7281 | 0.6645 | |
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| 1.7704 | 13.0 | 2340 | 1.6984 | 0.6685 | |
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| 1.7431 | 14.0 | 2520 | 1.6807 | 0.6734 | |
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| 1.7293 | 15.0 | 2700 | 1.6749 | 0.6729 | |
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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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