---
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_m080_tiny-stories_1024
  results:
  - task:
      name: Causal Language Modeling
      type: text-generation
    dataset:
      name: roneneldan/TinyStories
      type: roneneldan/TinyStories
    metrics:
    - name: Accuracy
      type: accuracy
      value: 0.6787833469368093
---

<!-- 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/runs/3tjo6ipp)
# gpt2_m080_tiny-stories_1024

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: 1.2099
- Accuracy: 0.6788

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.8882        | 0.0522 | 1000  | 2.4481          | 0.4477   |
| 1.9734        | 0.1043 | 2000  | 1.7975          | 0.5687   |
| 1.7272        | 0.1565 | 3000  | 1.6134          | 0.6017   |
| 1.6087        | 0.2086 | 4000  | 1.5135          | 0.6195   |
| 1.5337        | 0.2608 | 5000  | 1.4512          | 0.6313   |
| 1.4808        | 0.3129 | 6000  | 1.4058          | 0.6399   |
| 1.444         | 0.3651 | 7000  | 1.3705          | 0.6466   |
| 1.4094        | 0.4173 | 8000  | 1.3408          | 0.6524   |
| 1.385         | 0.4694 | 9000  | 1.3191          | 0.6566   |
| 1.364         | 0.5216 | 10000 | 1.2988          | 0.6608   |
| 1.3413        | 0.5737 | 11000 | 1.2813          | 0.6643   |
| 1.3267        | 0.6259 | 12000 | 1.2677          | 0.6669   |
| 1.3161        | 0.6780 | 13000 | 1.2534          | 0.6697   |
| 1.3083        | 0.7302 | 14000 | 1.2439          | 0.6717   |
| 1.2955        | 0.7824 | 15000 | 1.2366          | 0.6731   |
| 1.285         | 0.8345 | 16000 | 1.2262          | 0.6754   |
| 1.2796        | 0.8867 | 17000 | 1.2194          | 0.6767   |
| 1.271         | 0.9388 | 18000 | 1.2133          | 0.6780   |
| 1.2678        | 0.9910 | 19000 | 1.2101          | 0.6787   |


### Framework versions

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