---
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_u060_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: 0.6824684349371644
---

<!-- 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/km9fib7s)
# gpt2_u060_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: 1.1944
- Accuracy: 0.6825

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.9072        | 0.0521 | 1000  | 2.4167          | 0.4556   |
| 1.9548        | 0.1043 | 2000  | 1.7778          | 0.5734   |
| 1.707         | 0.1564 | 3000  | 1.5956          | 0.6059   |
| 1.589         | 0.2085 | 4000  | 1.4949          | 0.6241   |
| 1.5186        | 0.2607 | 5000  | 1.4333          | 0.6353   |
| 1.463         | 0.3128 | 6000  | 1.3858          | 0.6444   |
| 1.4279        | 0.3649 | 7000  | 1.3521          | 0.6508   |
| 1.3932        | 0.4171 | 8000  | 1.3245          | 0.6564   |
| 1.3687        | 0.4692 | 9000  | 1.3019          | 0.6604   |
| 1.3498        | 0.5213 | 10000 | 1.2831          | 0.6644   |
| 1.3315        | 0.5735 | 11000 | 1.2661          | 0.6677   |
| 1.3141        | 0.6256 | 12000 | 1.2517          | 0.6706   |
| 1.3006        | 0.6778 | 13000 | 1.2390          | 0.6731   |
| 1.2872        | 0.7299 | 14000 | 1.2279          | 0.6754   |
| 1.2757        | 0.7820 | 15000 | 1.2187          | 0.6773   |
| 1.2688        | 0.8342 | 16000 | 1.2117          | 0.6788   |
| 1.2609        | 0.8863 | 17000 | 1.2041          | 0.6803   |
| 1.2572        | 0.9384 | 18000 | 1.1983          | 0.6817   |
| 1.2517        | 0.9906 | 19000 | 1.1945          | 0.6825   |


### Framework versions

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