metadata
tags:
- generated_from_trainer
datasets:
- roneneldan/TinyStories
metrics:
- accuracy
model-index:
- name: gpt2_m080_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: 0.6787833469368093
gpt2_m080_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: 1.2099
- Accuracy: 0.6788
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 |
|---|---|---|---|---|
| 2.8882 | 0.0522 | 1000 | 2.4481 | 0.4477 |
| 1.9734 | 0.1043 | 2000 | 1.7975 | 0.5687 |
| 1.7272 | 0.1565 | 3000 | 1.6134 | 0.6017 |
| 1.6087 | 0.2086 | 4000 | 1.5135 | 0.6195 |
| 1.5337 | 0.2608 | 5000 | 1.4512 | 0.6313 |
| 1.4808 | 0.3129 | 6000 | 1.4058 | 0.6399 |
| 1.444 | 0.3651 | 7000 | 1.3705 | 0.6466 |
| 1.4094 | 0.4173 | 8000 | 1.3408 | 0.6524 |
| 1.385 | 0.4694 | 9000 | 1.3191 | 0.6566 |
| 1.364 | 0.5216 | 10000 | 1.2988 | 0.6608 |
| 1.3413 | 0.5737 | 11000 | 1.2813 | 0.6643 |
| 1.3267 | 0.6259 | 12000 | 1.2677 | 0.6669 |
| 1.3161 | 0.6780 | 13000 | 1.2534 | 0.6697 |
| 1.3083 | 0.7302 | 14000 | 1.2439 | 0.6717 |
| 1.2955 | 0.7824 | 15000 | 1.2366 | 0.6731 |
| 1.285 | 0.8345 | 16000 | 1.2262 | 0.6754 |
| 1.2796 | 0.8867 | 17000 | 1.2194 | 0.6767 |
| 1.271 | 0.9388 | 18000 | 1.2133 | 0.6780 |
| 1.2678 | 0.9910 | 19000 | 1.2101 | 0.6787 |
Framework versions
- Transformers 4.42.3
- Pytorch 2.2.2+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1