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--- |
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license: apache-2.0 |
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base_model: google/bert_uncased_L-4_H-256_A-4 |
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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-4_H-256_A-4_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: 0.8362026561731432 |
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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-4_H-256_A-4_massive |
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This model is a fine-tuned version of [google/bert_uncased_L-4_H-256_A-4](https://huggingface.co/google/bert_uncased_L-4_H-256_A-4) on the massive dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.7252 |
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- Accuracy: 0.8362 |
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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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| 3.5031 | 1.0 | 180 | 2.8542 | 0.4437 | |
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| 2.5403 | 2.0 | 360 | 2.0782 | 0.6394 | |
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| 1.928 | 3.0 | 540 | 1.6213 | 0.7118 | |
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| 1.542 | 4.0 | 720 | 1.3355 | 0.7526 | |
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| 1.2771 | 5.0 | 900 | 1.1556 | 0.7801 | |
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| 1.0852 | 6.0 | 1080 | 1.0223 | 0.7964 | |
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| 0.939 | 7.0 | 1260 | 0.9331 | 0.8047 | |
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| 0.8352 | 8.0 | 1440 | 0.8670 | 0.8146 | |
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| 0.7522 | 9.0 | 1620 | 0.8184 | 0.8190 | |
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| 0.6847 | 10.0 | 1800 | 0.7887 | 0.8254 | |
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| 0.6369 | 11.0 | 1980 | 0.7578 | 0.8254 | |
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| 0.5943 | 12.0 | 2160 | 0.7413 | 0.8323 | |
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| 0.5652 | 13.0 | 2340 | 0.7288 | 0.8328 | |
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| 0.5486 | 14.0 | 2520 | 0.7252 | 0.8362 | |
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| 0.5394 | 15.0 | 2700 | 0.7190 | 0.8357 | |
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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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