---
license: mit
base_model: gpt2
tags:
- generated_from_trainer
model-index:
- name: pretraining7
  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. -->

# pretraining7

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: 2.9516

## 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: 0.0006
- 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: inverse_sqrt
- lr_scheduler_warmup_steps: 250
- training_steps: 1500
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch  | Step | Validation Loss |
|:-------------:|:------:|:----:|:---------------:|
| 9.1748        | 0.1830 | 50   | 7.4163          |
| 6.7378        | 0.3660 | 100  | 6.2275          |
| 5.9659        | 0.5490 | 150  | 5.6559          |
| 5.4898        | 0.7321 | 200  | 5.2576          |
| 5.1248        | 0.9151 | 250  | 4.9392          |
| 4.7951        | 1.0981 | 300  | 4.6297          |
| 4.4843        | 1.2811 | 350  | 4.3591          |
| 4.2178        | 1.4641 | 400  | 4.0591          |
| 3.9729        | 1.6471 | 450  | 3.7843          |
| 3.766         | 1.8302 | 500  | 3.6225          |
| 3.6046        | 2.0132 | 550  | 3.5064          |
| 3.41          | 2.1962 | 600  | 3.4262          |
| 3.3702        | 2.3792 | 650  | 3.3577          |
| 3.309         | 2.5622 | 700  | 3.3027          |
| 3.2562        | 2.7452 | 750  | 3.2583          |
| 3.2027        | 2.9283 | 800  | 3.2192          |
| 3.1139        | 3.1113 | 850  | 3.1779          |
| 3.0442        | 3.2943 | 900  | 3.1549          |
| 3.0144        | 3.4773 | 950  | 3.1266          |
| 3.0016        | 3.6603 | 1000 | 3.0997          |
| 3.0001        | 3.8433 | 1050 | 3.0770          |
| 2.9655        | 4.0264 | 1100 | 3.0554          |
| 2.8328        | 4.2094 | 1150 | 3.0422          |
| 2.8343        | 4.3924 | 1200 | 3.0261          |
| 2.8266        | 4.5754 | 1250 | 3.0105          |
| 2.8236        | 4.7584 | 1300 | 2.9962          |
| 2.8194        | 4.9414 | 1350 | 2.9807          |
| 2.7161        | 5.1245 | 1400 | 2.9717          |
| 2.6842        | 5.3075 | 1450 | 2.9632          |
| 2.6898        | 5.4905 | 1500 | 2.9516          |


### Framework versions

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