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---
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
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/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
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