---
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_u100_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: 0.6900891972857721
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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[<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/q6cikc5d)
# gpt2_u100_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: 1.1688
- Accuracy: 0.6901

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.8305        | 0.0505 | 1000  | 2.3790          | 0.4650   |
| 1.9272        | 0.1009 | 2000  | 1.7501          | 0.5809   |
| 1.6793        | 0.1514 | 3000  | 1.5689          | 0.6136   |
| 1.5605        | 0.2018 | 4000  | 1.4699          | 0.6316   |
| 1.4891        | 0.2523 | 5000  | 1.4112          | 0.6422   |
| 1.4391        | 0.3028 | 6000  | 1.3646          | 0.6514   |
| 1.3995        | 0.3532 | 7000  | 1.3317          | 0.6575   |
| 1.3707        | 0.4037 | 8000  | 1.3021          | 0.6631   |
| 1.3424        | 0.4541 | 9000  | 1.2806          | 0.6675   |
| 1.3242        | 0.5046 | 10000 | 1.2613          | 0.6714   |
| 1.3058        | 0.5551 | 11000 | 1.2435          | 0.6748   |
| 1.2888        | 0.6055 | 12000 | 1.2291          | 0.6777   |
| 1.2748        | 0.6560 | 13000 | 1.2178          | 0.6801   |
| 1.2654        | 0.7064 | 14000 | 1.2077          | 0.6821   |
| 1.2549        | 0.7569 | 15000 | 1.1964          | 0.6843   |
| 1.2459        | 0.8073 | 16000 | 1.1878          | 0.6860   |
| 1.2385        | 0.8578 | 17000 | 1.1819          | 0.6873   |
| 1.2286        | 0.9083 | 18000 | 1.1756          | 0.6886   |
| 1.2246        | 0.9587 | 19000 | 1.1708          | 0.6896   |


### Framework versions

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