metadata
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_m030_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: 0.6756425005551174
gpt2_m030_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: 1.2217
- Accuracy: 0.6756
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 |
|---|---|---|---|---|
| 2.9308 | 0.0525 | 1000 | 2.4752 | 0.4408 |
| 1.9919 | 0.1050 | 2000 | 1.8136 | 0.5648 |
| 1.7406 | 0.1575 | 3000 | 1.6235 | 0.5984 |
| 1.6185 | 0.2101 | 4000 | 1.5258 | 0.6165 |
| 1.5461 | 0.2626 | 5000 | 1.4625 | 0.6282 |
| 1.4955 | 0.3151 | 6000 | 1.4170 | 0.6368 |
| 1.4553 | 0.3676 | 7000 | 1.3824 | 0.6433 |
| 1.4218 | 0.4201 | 8000 | 1.3532 | 0.6492 |
| 1.3986 | 0.4726 | 9000 | 1.3305 | 0.6537 |
| 1.3722 | 0.5252 | 10000 | 1.3100 | 0.6575 |
| 1.3573 | 0.5777 | 11000 | 1.2934 | 0.6608 |
| 1.3448 | 0.6302 | 12000 | 1.2785 | 0.6639 |
| 1.3291 | 0.6827 | 13000 | 1.2657 | 0.6665 |
| 1.3174 | 0.7352 | 14000 | 1.2551 | 0.6686 |
| 1.3052 | 0.7877 | 15000 | 1.2463 | 0.6704 |
| 1.2968 | 0.8402 | 16000 | 1.2366 | 0.6725 |
| 1.2856 | 0.8928 | 17000 | 1.2308 | 0.6735 |
| 1.2817 | 0.9453 | 18000 | 1.2249 | 0.6749 |
| 1.2814 | 0.9978 | 19000 | 1.2216 | 0.6757 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1