---
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_u040_tiny-stories_1024_dpos
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: roneneldan/TinyStories
      type: roneneldan/TinyStories
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6809154122817009
---

<!-- 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. -->

[<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/scads-nlp/morph-gpt_gpt2_tiny-stories_dpos/runs/gh64e6as)
# gpt2_u040_tiny-stories_1024_dpos

This model is a fine-tuned version of [](https://huggingface.co/) on the roneneldan/TinyStories dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2015
- Accuracy: 0.6809

## 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: 5e-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: 1.0

### Training results

| Training Loss | Epoch  | Step  | Validation Loss | Accuracy |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.8993        | 0.0523 | 1000  | 2.4128          | 0.4573   |
| 1.9582        | 0.1046 | 2000  | 1.7777          | 0.5731   |
| 1.7164        | 0.1569 | 3000  | 1.5985          | 0.6049   |
| 1.5976        | 0.2092 | 4000  | 1.5014          | 0.6224   |
| 1.5257        | 0.2615 | 5000  | 1.4399          | 0.6342   |
| 1.4723        | 0.3138 | 6000  | 1.3955          | 0.6425   |
| 1.4337        | 0.3661 | 7000  | 1.3618          | 0.6489   |
| 1.4068        | 0.4184 | 8000  | 1.3318          | 0.6549   |
| 1.3766        | 0.4707 | 9000  | 1.3082          | 0.6594   |
| 1.3567        | 0.5230 | 10000 | 1.2884          | 0.6632   |
| 1.3373        | 0.5753 | 11000 | 1.2717          | 0.6667   |
| 1.3231        | 0.6275 | 12000 | 1.2593          | 0.6692   |
| 1.3101        | 0.6798 | 13000 | 1.2451          | 0.6717   |
| 1.2962        | 0.7321 | 14000 | 1.2344          | 0.6740   |
| 1.2842        | 0.7844 | 15000 | 1.2259          | 0.6759   |
| 1.2752        | 0.8367 | 16000 | 1.2178          | 0.6776   |
| 1.2718        | 0.8890 | 17000 | 1.2103          | 0.6789   |
| 1.2628        | 0.9413 | 18000 | 1.2050          | 0.6803   |
| 1.2576        | 0.9936 | 19000 | 1.2016          | 0.6809   |


### Framework versions

- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1