---
base_model: ai-forever/rugpt3medium_based_on_gpt2
tags:
- generated_from_trainer
model-index:
- name: my_rugpt3medium_finetune
  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. -->

# my_rugpt3medium_finetune

This model is a fine-tuned version of [ai-forever/rugpt3medium_based_on_gpt2](https://huggingface.co/ai-forever/rugpt3medium_based_on_gpt2) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.9269

## 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: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 3
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 1000
- num_epochs: 25
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 3.601         | 1.6   | 25   | 3.6157          |
| 3.601         | 3.19  | 50   | 3.6010          |
| 3.5542        | 4.79  | 75   | 3.5621          |
| 3.5309        | 6.38  | 100  | 3.5117          |
| 3.496         | 7.98  | 125  | 3.4615          |
| 3.446         | 9.57  | 150  | 3.4173          |
| 3.34          | 11.17 | 175  | 3.3699          |
| 3.3581        | 12.77 | 200  | 3.3214          |
| 3.3136        | 14.36 | 225  | 3.2743          |
| 3.214         | 15.96 | 250  | 3.2227          |
| 3.2098        | 17.55 | 275  | 3.1738          |
| 3.1348        | 19.15 | 300  | 3.1153          |
| 3.0931        | 20.74 | 325  | 3.0561          |
| 3.0383        | 22.34 | 350  | 2.9922          |
| 2.9739        | 23.94 | 375  | 2.9269          |


### Framework versions

- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.0
- Tokenizers 0.15.0