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--- |
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library_name: transformers |
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language: |
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- en |
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license: apache-2.0 |
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base_model: google/bert_uncased_L-2_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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- glue |
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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-256_A-4_mnli |
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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: GLUE MNLI |
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type: glue |
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args: mnli |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.7332180634662328 |
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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-256_A-4_mnli |
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This model is a fine-tuned version of [google/bert_uncased_L-2_H-256_A-4](https://huggingface.co./google/bert_uncased_L-2_H-256_A-4) on the GLUE MNLI dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6492 |
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- Accuracy: 0.7332 |
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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: 256 |
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- eval_batch_size: 256 |
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- seed: 10 |
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- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
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- lr_scheduler_type: linear |
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- num_epochs: 50 |
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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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| 0.8512 | 1.0 | 1534 | 0.7602 | 0.6654 | |
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| 0.7432 | 2.0 | 3068 | 0.7031 | 0.6940 | |
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| 0.6912 | 3.0 | 4602 | 0.6761 | 0.7101 | |
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| 0.6524 | 4.0 | 6136 | 0.6655 | 0.7179 | |
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| 0.6224 | 5.0 | 7670 | 0.6699 | 0.7217 | |
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| 0.5935 | 6.0 | 9204 | 0.6757 | 0.7192 | |
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| 0.5689 | 7.0 | 10738 | 0.6650 | 0.7255 | |
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| 0.5458 | 8.0 | 12272 | 0.6831 | 0.7271 | |
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| 0.526 | 9.0 | 13806 | 0.6980 | 0.7222 | |
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| 0.5031 | 10.0 | 15340 | 0.7006 | 0.7258 | |
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| 0.4847 | 11.0 | 16874 | 0.7057 | 0.7250 | |
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| 0.4673 | 12.0 | 18408 | 0.7297 | 0.7264 | |
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### Framework versions |
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- Transformers 4.46.3 |
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- Pytorch 2.2.1+cu118 |
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- Datasets 2.17.0 |
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- Tokenizers 0.20.3 |
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