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--- |
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language: |
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- en |
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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: hBERTv2_new_pretrain_48_rte |
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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 RTE |
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type: glue |
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config: rte |
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split: validation |
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args: rte |
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metrics: |
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- name: Accuracy |
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type: accuracy |
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value: 0.5379061371841155 |
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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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# hBERTv2_new_pretrain_48_rte |
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This model is a fine-tuned version of [gokuls/bert_12_layer_model_v2_complete_training_new_48](https://huggingface.co/gokuls/bert_12_layer_model_v2_complete_training_new_48) on the GLUE RTE dataset. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.6901 |
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- Accuracy: 0.5379 |
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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: 4e-05 |
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- train_batch_size: 128 |
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- eval_batch_size: 128 |
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- seed: 10 |
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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: 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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| 0.7454 | 1.0 | 20 | 0.7895 | 0.4729 | |
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| 0.7171 | 2.0 | 40 | 0.6994 | 0.4729 | |
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| 0.701 | 3.0 | 60 | 0.6901 | 0.5379 | |
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| 0.6823 | 4.0 | 80 | 0.7257 | 0.5271 | |
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| 0.6383 | 5.0 | 100 | 0.7477 | 0.5379 | |
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| 0.5227 | 6.0 | 120 | 0.9450 | 0.5343 | |
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| 0.4559 | 7.0 | 140 | 1.1971 | 0.5235 | |
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| 0.3672 | 8.0 | 160 | 1.0455 | 0.5307 | |
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### Framework versions |
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- Transformers 4.29.2 |
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- Pytorch 1.14.0a0+410ce96 |
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- Datasets 2.12.0 |
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- Tokenizers 0.13.3 |
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