---
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_m010_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: 0.6768352947315901
---

<!-- 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/m7jmleqw)
# gpt2_m010_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: 1.2176
- Accuracy: 0.6768

## 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 |
|:-------------:|:------:|:-----:|:---------------:|:--------:|
| 2.9272        | 0.0524 | 1000  | 2.4654          | 0.4425   |
| 1.9903        | 0.1048 | 2000  | 1.8096          | 0.5657   |
| 1.7407        | 0.1572 | 3000  | 1.6194          | 0.5995   |
| 1.623         | 0.2096 | 4000  | 1.5257          | 0.6163   |
| 1.5462        | 0.2619 | 5000  | 1.4623          | 0.6285   |
| 1.4894        | 0.3143 | 6000  | 1.4145          | 0.6377   |
| 1.4533        | 0.3667 | 7000  | 1.3773          | 0.6449   |
| 1.4216        | 0.4191 | 8000  | 1.3503          | 0.6501   |
| 1.394         | 0.4715 | 9000  | 1.3288          | 0.6542   |
| 1.3762        | 0.5239 | 10000 | 1.3074          | 0.6585   |
| 1.3551        | 0.5763 | 11000 | 1.2899          | 0.6620   |
| 1.3385        | 0.6287 | 12000 | 1.2746          | 0.6650   |
| 1.323         | 0.6811 | 13000 | 1.2622          | 0.6676   |
| 1.318         | 0.7334 | 14000 | 1.2517          | 0.6698   |
| 1.3015        | 0.7858 | 15000 | 1.2416          | 0.6719   |
| 1.2967        | 0.8382 | 16000 | 1.2337          | 0.6734   |
| 1.2859        | 0.8906 | 17000 | 1.2269          | 0.6749   |
| 1.2785        | 0.9430 | 18000 | 1.2216          | 0.6760   |
| 1.2753        | 0.9954 | 19000 | 1.2178          | 0.6768   |


### Framework versions

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