transformers tensorboard safetensors gpt2 text-generation summarization generated_from_trainer base_model:ckiplab/gpt2-tiny-chinese base_model:finetune:ckiplab/gpt2-tiny-chinese license:gpl-3.0 autotrain_compatible text-generation-inference endpoints_compatible region:us
---
base_model: ckiplab/gpt2-tiny-chinese
library_name: transformers
license: gpl-3.0
tags:
- summarization
- generated_from_trainer
model-index:
- name: ADL_HW2_GPT2
  results: []
---

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[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/ov47z0tg)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/ov47z0tg)
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/djengo890-national-taiwan-university/ADL_HW2_RT_GPT2/runs/ov47z0tg)
# ADL_HW2_GPT2

This model is a fine-tuned version of [ckiplab/gpt2-tiny-chinese](https://huggingface.co/ckiplab/gpt2-tiny-chinese) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.4578

## 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: 5.6e-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: 8

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.02          | 1.0   | 543  | 3.6837          |
| 3.8249        | 2.0   | 1086 | 3.5804          |
| 3.7431        | 3.0   | 1629 | 3.5336          |
| 3.6958        | 4.0   | 2172 | 3.5036          |
| 3.6633        | 5.0   | 2715 | 3.4815          |
| 3.639         | 6.0   | 3258 | 3.4722          |
| 3.622         | 7.0   | 3801 | 3.4597          |
| 3.6095        | 8.0   | 4344 | 3.4578          |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1
