---
license: apache-2.0
base_model: albert/albert-large-v2
tags:
- generated_from_trainer
model-index:
- name: albert-albert-large-v2
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# albert-albert-large-v2

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.
It achieves the following results on the evaluation set:
- Loss: 0.0032

## Model Intent

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:
https://huggingface.co/datasets/siddharthl1293/engineering_design_facts


### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 1

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 0.0032        | 1.0   | 9378 | 0.0032          |

### Testing Results

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.
The average testing accuracy across 37,509 testing examples is 0.997.

### Framework versions

- Transformers 4.41.2
- Pytorch 2.3.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1