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--- |
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license: apache-2.0 |
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base_model: albert/albert-large-v2 |
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tags: |
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- generated_from_trainer |
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model-index: |
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- name: albert-albert-large-v2 |
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results: [] |
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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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# albert-albert-large-v2 |
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This model is a fine-tuned version of [albert/albert-large-v2](https://huggingface.co/albert/albert-large-v2) on the raw version of the dataset https://huggingface.co/datasets/siddharthl1293/engineering_design_facts. |
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It achieves the following results on the evaluation set: |
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- Loss: 0.0032 |
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## Model Intent |
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The model was trained to identify relationship tokens in a sentence when a pair of entities are marked. For more info, please go through the dataset description: |
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https://huggingface.co/datasets/siddharthl1293/engineering_design_facts |
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### Training hyperparameters |
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The following hyperparameters were used during training: |
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- learning_rate: 2e-05 |
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- train_batch_size: 32 |
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- eval_batch_size: 32 |
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- seed: 42 |
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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: 1 |
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### Training results |
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| Training Loss | Epoch | Step | Validation Loss | |
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|:-------------:|:-----:|:----:|:---------------:| |
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| 0.0032 | 1.0 | 9378 | 0.0032 | |
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### Testing Results |
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Testing accuracy was calculated on a test set wherein, all relationship tokens need to be identified in an example for the accuracy to be 1. |
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The average testing accuracy across 37,509 testing examples is 0.997. |
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### Framework versions |
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- Transformers 4.41.2 |
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- Pytorch 2.3.0+cu121 |
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- Datasets 2.20.0 |
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- Tokenizers 0.19.1 |
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