---
license: apache-2.0
base_model: albert-base-v2
tags:
- generated_from_trainer
datasets:
- squad
model-index:
- name: FN_JLL-Hackathon-Fine-Tuned_QA-ALBERT-SQuAD
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# FN_JLL-Hackathon-Fine-Tuned_QA-ALBERT-SQuAD

This model is a fine-tuned version of [albert-base-v2](https://huggingface.co./albert-base-v2) on the squad dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3848

## Model description

More information needed

## Intended uses & limitations

More information needed

## Training and evaluation data

More information needed

## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log        | 1.0   | 25   | 2.4216          |
| No log        | 2.0   | 50   | 1.5827          |
| No log        | 3.0   | 75   | 1.3848          |


### Framework versions

- Transformers 4.33.1
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.13.3