---
license: mit
tags:
- generated_from_trainer
base_model: openai-community/gpt2
model-index:
- name: gpt2-finetuned-mcqa-sciq
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->

# gpt2-finetuned-mcqa-sciq

This model is a fine-tuned version of [openai-community/gpt2](https://huggingface.co/openai-community/gpt2) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.3533
- Bertscore Precision: 0.1082
- Bertscore Recall: 0.1141
- Bertscore F1: 0.1111

## 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: 3e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Bertscore Precision | Bertscore Recall | Bertscore F1 |
|:-------------:|:------:|:-----:|:---------------:|:-------------------:|:----------------:|:------------:|
| 4.4695        | 0.9999 | 5839  | 2.3612          | 0.1082              | 0.1140           | 0.1110       |
| 4.0507        | 2.0    | 11679 | 2.3533          | 0.1082              | 0.1141           | 0.1111       |
| 3.8779        | 2.9999 | 17518 | 2.3820          | 0.1080              | 0.1140           | 0.1110       |
| 3.2852        | 4.0    | 23358 | 2.4208          | 0.1080              | 0.1140           | 0.1109       |
| 3.6416        | 4.9999 | 29197 | 2.4768          | 0.1079              | 0.1139           | 0.1108       |
| 2.9843        | 6.0    | 35037 | 2.5445          | 0.1079              | 0.1139           | 0.1108       |
| 2.8509        | 6.9999 | 40876 | 2.6094          | 0.1079              | 0.1139           | 0.1108       |
| 2.6932        | 8.0    | 46716 | 2.6658          | 0.1078              | 0.1138           | 0.1107       |
| 2.5309        | 8.9999 | 52555 | 2.7283          | 0.1078              | 0.1138           | 0.1107       |
| 2.5619        | 9.9991 | 58390 | 2.7585          | 0.1078              | 0.1138           | 0.1107       |


### Framework versions

- Transformers 4.40.2
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1