generated_from_trainer dataset:scitldr base_model:gpt2-large license:mit region:us
---
license: mit
base_model: gpt2-large
tags:
- generated_from_trainer
datasets:
- scitldr
model-index:
- name: uplimit-project-3-gpt2-large
  results: []
---

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# uplimit-project-3-gpt2-large

This model is a fine-tuned version of [gpt2-large](https://huggingface.co/gpt2-large) on the scitldr dataset.
It achieves the following results on the evaluation set:
- Loss: 3.5296

## 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: 0.001
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- 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 |
|:-------------:|:-----:|:-----:|:---------------:|
| 1.8474        | 0.4   | 800   | 2.7175          |
| 1.8784        | 0.8   | 1600  | 2.6618          |
| 1.6307        | 1.2   | 2400  | 2.7737          |
| 2.0121        | 1.61  | 3200  | 2.6673          |
| 2.033         | 2.01  | 4000  | 2.7799          |
| 1.8416        | 2.41  | 4800  | 2.8229          |
| 1.7133        | 2.81  | 5600  | 2.7827          |
| 1.681         | 3.21  | 6400  | 2.9556          |
| 1.5638        | 3.61  | 7200  | 2.9581          |
| 1.3838        | 4.02  | 8000  | 2.9749          |
| 1.2711        | 4.42  | 8800  | 2.9982          |
| 1.2488        | 4.82  | 9600  | 2.9858          |
| 0.9192        | 5.22  | 10400 | 3.1093          |
| 0.914         | 5.62  | 11200 | 3.1497          |
| 0.6613        | 6.02  | 12000 | 3.1170          |
| 0.6696        | 6.43  | 12800 | 3.1780          |
| 0.8281        | 6.83  | 13600 | 3.1630          |
| 0.3944        | 7.23  | 14400 | 3.3688          |
| 0.4512        | 7.63  | 15200 | 3.3493          |
| 0.313         | 8.03  | 16000 | 3.4182          |
| 0.3008        | 8.43  | 16800 | 3.4404          |
| 0.3054        | 8.84  | 17600 | 3.4577          |
| 0.2112        | 9.24  | 18400 | 3.5108          |
| 0.2435        | 9.64  | 19200 | 3.5296          |


### Framework versions

- Transformers 4.34.1
- Pytorch 2.1.0+cu118
- Datasets 2.14.6
- Tokenizers 0.14.1
