---
base_model: NlpHUST/gpt-neo-vi-small
tags:
- generated_from_trainer
model-index:
- name: vi_gpt_poem_
  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. -->

# vi_gpt_poem_

This model is a fine-tuned version of [NlpHUST/gpt-neo-vi-small](https://huggingface.co/NlpHUST/gpt-neo-vi-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1334

## 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: 1e-05
- train_batch_size: 42
- eval_batch_size: 42
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 250
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch    | Step  | Validation Loss |
|:-------------:|:--------:|:-----:|:---------------:|
| 6.8634        | 3.9683   | 500   | 6.1900          |
| 4.7999        | 7.9365   | 1000  | 3.4039          |
| 2.7473        | 11.9048  | 1500  | 2.5766          |
| 2.2513        | 15.8730  | 2000  | 2.2051          |
| 1.9426        | 19.8413  | 2500  | 1.9113          |
| 1.7059        | 23.8095  | 3000  | 1.6723          |
| 1.5333        | 27.7778  | 3500  | 1.5196          |
| 1.3996        | 31.7460  | 4000  | 1.4060          |
| 1.3066        | 35.7143  | 4500  | 1.3193          |
| 1.228         | 39.6825  | 5000  | 1.2513          |
| 1.1642        | 43.6508  | 5500  | 1.2000          |
| 1.1191        | 47.6190  | 6000  | 1.1607          |
| 1.0825        | 51.5873  | 6500  | 1.1295          |
| 1.0483        | 55.5556  | 7000  | 1.1036          |
| 1.0203        | 59.5238  | 7500  | 1.0818          |
| 0.9967        | 63.4921  | 8000  | 1.0631          |
| 0.9745        | 67.4603  | 8500  | 1.0471          |
| 0.9552        | 71.4286  | 9000  | 1.0332          |
| 0.9362        | 75.3968  | 9500  | 1.0208          |
| 0.9165        | 79.3651  | 10000 | 1.0098          |
| 0.8977        | 83.3333  | 10500 | 1.0002          |
| 0.8846        | 87.3016  | 11000 | 0.9915          |
| 0.8641        | 91.2698  | 11500 | 0.9838          |
| 0.8478        | 95.2381  | 12000 | 0.9779          |
| 0.8286        | 99.2063  | 12500 | 0.9721          |
| 0.811         | 103.1746 | 13000 | 0.9677          |
| 0.7916        | 107.1429 | 13500 | 0.9644          |
| 0.7721        | 111.1111 | 14000 | 0.9625          |
| 0.7513        | 115.0794 | 14500 | 0.9616          |
| 0.7292        | 119.0476 | 15000 | 0.9617          |
| 0.7066        | 123.0159 | 15500 | 0.9622          |
| 0.683         | 126.9841 | 16000 | 0.9639          |
| 0.6582        | 130.9524 | 16500 | 0.9661          |
| 0.632         | 134.9206 | 17000 | 0.9690          |
| 0.6047        | 138.8889 | 17500 | 0.9727          |
| 0.5769        | 142.8571 | 18000 | 0.9763          |
| 0.548         | 146.8254 | 18500 | 0.9802          |
| 0.5169        | 150.7937 | 19000 | 0.9844          |
| 0.4863        | 154.7619 | 19500 | 0.9887          |
| 0.4536        | 158.7302 | 20000 | 0.9936          |
| 0.4223        | 162.6984 | 20500 | 0.9975          |
| 0.3891        | 166.6667 | 21000 | 1.0022          |
| 0.3571        | 170.6349 | 21500 | 1.0071          |
| 0.3256        | 174.6032 | 22000 | 1.0118          |
| 0.2946        | 178.5714 | 22500 | 1.0164          |
| 0.2642        | 182.5397 | 23000 | 1.0221          |
| 0.2345        | 186.5079 | 23500 | 1.0271          |
| 0.2069        | 190.4762 | 24000 | 1.0331          |
| 0.1806        | 194.4444 | 24500 | 1.0393          |
| 0.1565        | 198.4127 | 25000 | 1.0462          |
| 0.1351        | 202.3810 | 25500 | 1.0527          |
| 0.1153        | 206.3492 | 26000 | 1.0605          |
| 0.0984        | 210.3175 | 26500 | 1.0679          |
| 0.0842        | 214.2857 | 27000 | 1.0758          |
| 0.0721        | 218.2540 | 27500 | 1.0827          |
| 0.0627        | 222.2222 | 28000 | 1.0906          |
| 0.0555        | 226.1905 | 28500 | 1.0978          |
| 0.0495        | 230.1587 | 29000 | 1.1043          |
| 0.045         | 234.1270 | 29500 | 1.1107          |
| 0.0412        | 238.0952 | 30000 | 1.1166          |
| 0.0382        | 242.0635 | 30500 | 1.1228          |
| 0.0356        | 246.0317 | 31000 | 1.1275          |
| 0.0335        | 250.0    | 31500 | 1.1334          |


### Framework versions

- Transformers 4.40.0
- Pytorch 2.1.2
- Datasets 2.16.1
- Tokenizers 0.19.1