O0503HMA15
This model is a fine-tuned version of allenai/OLMo-1B on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.0219
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: 0.0003
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 16
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine_with_restarts
- lr_scheduler_warmup_steps: 100
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.5411 | 0.09 | 10 | 0.2074 |
0.1647 | 0.18 | 20 | 0.1574 |
0.1491 | 0.27 | 30 | 0.1606 |
0.1576 | 0.36 | 40 | 0.1526 |
0.1514 | 0.45 | 50 | 0.1550 |
0.1545 | 0.54 | 60 | 0.1516 |
0.1533 | 0.63 | 70 | 0.1479 |
0.1494 | 0.73 | 80 | 0.1583 |
0.1489 | 0.82 | 90 | 0.1499 |
0.1508 | 0.91 | 100 | 0.1535 |
0.1526 | 1.0 | 110 | 0.1510 |
0.1471 | 1.09 | 120 | 0.1501 |
0.1475 | 1.18 | 130 | 0.1502 |
0.148 | 1.27 | 140 | 0.1500 |
0.15 | 1.36 | 150 | 0.1507 |
0.1459 | 1.45 | 160 | 0.1479 |
0.1415 | 1.54 | 170 | 0.1328 |
0.1227 | 1.63 | 180 | 0.0874 |
0.0794 | 1.72 | 190 | 0.2132 |
0.0874 | 1.81 | 200 | 0.0840 |
0.0651 | 1.9 | 210 | 0.0487 |
0.0567 | 1.99 | 220 | 0.0494 |
0.0482 | 2.08 | 230 | 0.0400 |
0.0319 | 2.18 | 240 | 0.0300 |
0.0251 | 2.27 | 250 | 0.0288 |
0.0293 | 2.36 | 260 | 0.0271 |
0.0326 | 2.45 | 270 | 0.0243 |
0.0196 | 2.54 | 280 | 0.0237 |
0.027 | 2.63 | 290 | 0.0231 |
0.0255 | 2.72 | 300 | 0.0237 |
0.0225 | 2.81 | 310 | 0.0223 |
0.0236 | 2.9 | 320 | 0.0220 |
0.024 | 2.99 | 330 | 0.0219 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
Model tree for Litzy619/O0503HMA15
Base model
allenai/OLMo-1B