metadata
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
gpt2_m010_tiny-stories_1024
This model is a fine-tuned version of 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