|
|
--- |
|
|
library_name: peft |
|
|
license: mit |
|
|
base_model: gpt2 |
|
|
tags: |
|
|
- generated_from_trainer |
|
|
model-index: |
|
|
- name: Se124M100KInfKeyValue |
|
|
results: [] |
|
|
--- |
|
|
|
|
|
<!-- 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. --> |
|
|
|
|
|
# Se124M100KInfKeyValue |
|
|
|
|
|
This model is a fine-tuned version of [gpt2](https://huggingface.co/gpt2) on an unknown dataset. |
|
|
It achieves the following results on the evaluation set: |
|
|
- Loss: 0.4826 |
|
|
|
|
|
## 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: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments |
|
|
- lr_scheduler_type: linear |
|
|
- num_epochs: 50 |
|
|
- mixed_precision_training: Native AMP |
|
|
|
|
|
### Training results |
|
|
|
|
|
| Training Loss | Epoch | Step | Validation Loss | |
|
|
|:-------------:|:-----:|:------:|:---------------:| |
|
|
| 0.1533 | 1.0 | 2090 | 0.5677 | |
|
|
| 0.141 | 2.0 | 4180 | 0.5401 | |
|
|
| 0.1401 | 3.0 | 6270 | 0.5321 | |
|
|
| 0.1351 | 4.0 | 8360 | 0.5224 | |
|
|
| 0.1361 | 5.0 | 10450 | 0.5209 | |
|
|
| 0.134 | 6.0 | 12540 | 0.5155 | |
|
|
| 0.1315 | 7.0 | 14630 | 0.5118 | |
|
|
| 0.1304 | 8.0 | 16720 | 0.5085 | |
|
|
| 0.1299 | 9.0 | 18810 | 0.5067 | |
|
|
| 0.1294 | 10.0 | 20900 | 0.5066 | |
|
|
| 0.1309 | 11.0 | 22990 | 0.5030 | |
|
|
| 0.129 | 12.0 | 25080 | 0.5004 | |
|
|
| 0.1292 | 13.0 | 27170 | 0.4999 | |
|
|
| 0.1309 | 14.0 | 29260 | 0.4985 | |
|
|
| 0.1312 | 15.0 | 31350 | 0.4974 | |
|
|
| 0.1275 | 16.0 | 33440 | 0.4963 | |
|
|
| 0.1265 | 17.0 | 35530 | 0.4950 | |
|
|
| 0.1276 | 18.0 | 37620 | 0.4936 | |
|
|
| 0.1247 | 19.0 | 39710 | 0.4931 | |
|
|
| 0.1268 | 20.0 | 41800 | 0.4919 | |
|
|
| 0.1273 | 21.0 | 43890 | 0.4914 | |
|
|
| 0.1284 | 22.0 | 45980 | 0.4907 | |
|
|
| 0.1276 | 23.0 | 48070 | 0.4898 | |
|
|
| 0.1284 | 24.0 | 50160 | 0.4894 | |
|
|
| 0.1263 | 25.0 | 52250 | 0.4894 | |
|
|
| 0.1264 | 26.0 | 54340 | 0.4888 | |
|
|
| 0.1257 | 27.0 | 56430 | 0.4881 | |
|
|
| 0.1292 | 28.0 | 58520 | 0.4875 | |
|
|
| 0.1262 | 29.0 | 60610 | 0.4874 | |
|
|
| 0.1272 | 30.0 | 62700 | 0.4867 | |
|
|
| 0.1252 | 31.0 | 64790 | 0.4864 | |
|
|
| 0.1261 | 32.0 | 66880 | 0.4859 | |
|
|
| 0.1262 | 33.0 | 68970 | 0.4858 | |
|
|
| 0.1256 | 34.0 | 71060 | 0.4849 | |
|
|
| 0.1251 | 35.0 | 73150 | 0.4847 | |
|
|
| 0.1263 | 36.0 | 75240 | 0.4843 | |
|
|
| 0.1266 | 37.0 | 77330 | 0.4843 | |
|
|
| 0.125 | 38.0 | 79420 | 0.4842 | |
|
|
| 0.1248 | 39.0 | 81510 | 0.4840 | |
|
|
| 0.126 | 40.0 | 83600 | 0.4837 | |
|
|
| 0.1239 | 41.0 | 85690 | 0.4831 | |
|
|
| 0.1246 | 42.0 | 87780 | 0.4837 | |
|
|
| 0.1241 | 43.0 | 89870 | 0.4830 | |
|
|
| 0.1259 | 44.0 | 91960 | 0.4829 | |
|
|
| 0.1275 | 45.0 | 94050 | 0.4828 | |
|
|
| 0.1258 | 46.0 | 96140 | 0.4826 | |
|
|
| 0.1265 | 47.0 | 98230 | 0.4828 | |
|
|
| 0.1235 | 48.0 | 100320 | 0.4827 | |
|
|
| 0.1255 | 49.0 | 102410 | 0.4827 | |
|
|
| 0.1245 | 50.0 | 104500 | 0.4826 | |
|
|
|
|
|
|
|
|
### Framework versions |
|
|
|
|
|
- PEFT 0.15.1 |
|
|
- Transformers 4.51.3 |
|
|
- Pytorch 2.6.0+cu118 |
|
|
- Datasets 3.5.0 |
|
|
- Tokenizers 0.21.1 |
