---
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_m070_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: 0.6783595560713086
---

<!-- 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/runs/shwmemvo)
# gpt2_m070_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: 1.2096
- Accuracy: 0.6784

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.8977        | 0.0523 | 1000  | 2.4285          | 0.4506   |
| 1.9691        | 0.1045 | 2000  | 1.7883          | 0.5700   |
| 1.7235        | 0.1568 | 3000  | 1.6068          | 0.6021   |
| 1.6024        | 0.2091 | 4000  | 1.5058          | 0.6207   |
| 1.5325        | 0.2613 | 5000  | 1.4471          | 0.6315   |
| 1.481         | 0.3136 | 6000  | 1.4035          | 0.6400   |
| 1.4382        | 0.3659 | 7000  | 1.3690          | 0.6468   |
| 1.4083        | 0.4181 | 8000  | 1.3372          | 0.6527   |
| 1.3835        | 0.4704 | 9000  | 1.3157          | 0.6568   |
| 1.3618        | 0.5227 | 10000 | 1.2963          | 0.6608   |
| 1.3439        | 0.5750 | 11000 | 1.2785          | 0.6642   |
| 1.3279        | 0.6272 | 12000 | 1.2658          | 0.6668   |
| 1.3158        | 0.6795 | 13000 | 1.2528          | 0.6693   |
| 1.3022        | 0.7318 | 14000 | 1.2427          | 0.6714   |
| 1.295         | 0.7840 | 15000 | 1.2337          | 0.6733   |
| 1.285         | 0.8363 | 16000 | 1.2253          | 0.6751   |
| 1.2774        | 0.8886 | 17000 | 1.2190          | 0.6765   |
| 1.2734        | 0.9408 | 18000 | 1.2134          | 0.6776   |
| 1.2705        | 0.9931 | 19000 | 1.2098          | 0.6783   |


### Framework versions

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