---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: polynomial_1500_5e-4
  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. -->

# polynomial_1500_5e-4

This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 3.0244

## 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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 10
- total_train_batch_size: 320
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: polynomial
- lr_scheduler_warmup_steps: 250
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 9.2753        | 0.2175 | 50   | 7.6380          |
| 6.8812        | 0.4350 | 100  | 6.3560          |
| 6.0809        | 0.6525 | 150  | 5.7615          |
| 5.5903        | 0.8699 | 200  | 5.3682          |
| 5.2166        | 1.0874 | 250  | 5.0450          |
| 4.8887        | 1.3049 | 300  | 4.7443          |
| 4.6064        | 1.5224 | 350  | 4.4729          |
| 4.3711        | 1.7399 | 400  | 4.2030          |
| 4.1277        | 1.9574 | 450  | 3.9282          |
| 3.8099        | 2.1749 | 500  | 3.7320          |
| 3.6679        | 2.3923 | 550  | 3.6049          |
| 3.5513        | 2.6098 | 600  | 3.5031          |
| 3.4651        | 2.8273 | 650  | 3.4318          |
| 3.3797        | 3.0448 | 700  | 3.3644          |
| 3.2388        | 3.2623 | 750  | 3.3170          |
| 3.2017        | 3.4798 | 800  | 3.2766          |
| 3.173         | 3.6973 | 850  | 3.2426          |
| 3.143         | 3.9147 | 900  | 3.2054          |
| 3.0392        | 4.1322 | 950  | 3.1778          |
| 2.9809        | 4.3497 | 1000 | 3.1538          |
| 2.9564        | 4.5672 | 1050 | 3.1319          |
| 2.9576        | 4.7847 | 1100 | 3.1091          |
| 2.9375        | 5.0022 | 1150 | 3.0897          |
| 2.8071        | 5.2197 | 1200 | 3.0776          |
| 2.8145        | 5.4371 | 1250 | 3.0631          |
| 2.8042        | 5.6546 | 1300 | 3.0522          |
| 2.7851        | 5.8721 | 1350 | 3.0401          |
| 2.7462        | 6.0896 | 1400 | 3.0345          |
| 2.6936        | 6.3071 | 1450 | 3.0285          |
| 2.6984        | 6.5246 | 1500 | 3.0244          |


### Framework versions

- Transformers 4.40.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1