O0428HMA10
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: 0.1456
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 |
---|---|---|---|
1.7784 | 0.09 | 10 | 0.1810 |
0.1728 | 0.18 | 20 | 0.1533 |
0.1513 | 0.27 | 30 | 0.1702 |
0.1572 | 0.36 | 40 | 0.1529 |
0.151 | 0.45 | 50 | 0.1538 |
0.1533 | 0.54 | 60 | 0.1488 |
0.1495 | 0.63 | 70 | 0.1482 |
0.1488 | 0.73 | 80 | 0.1502 |
0.146 | 0.82 | 90 | 0.1498 |
0.1484 | 0.91 | 100 | 0.1495 |
0.15 | 1.0 | 110 | 0.1495 |
0.1436 | 1.09 | 120 | 0.1566 |
0.1355 | 1.18 | 130 | 0.1160 |
0.9465 | 1.27 | 140 | 7.4671 |
5.6519 | 1.36 | 150 | 3.3499 |
2.457 | 1.45 | 160 | 1.5871 |
1.842 | 1.54 | 170 | 0.8602 |
0.8488 | 1.63 | 180 | 0.5624 |
0.5347 | 1.72 | 190 | 0.4821 |
0.4016 | 1.81 | 200 | 0.3878 |
0.3025 | 1.9 | 210 | 0.2388 |
0.2251 | 1.99 | 220 | 0.2074 |
0.2096 | 2.08 | 230 | 0.2346 |
0.2117 | 2.18 | 240 | 0.1941 |
0.1817 | 2.27 | 250 | 0.1716 |
0.1629 | 2.36 | 260 | 0.1627 |
0.1533 | 2.45 | 270 | 0.1571 |
0.1503 | 2.54 | 280 | 0.1522 |
0.1453 | 2.63 | 290 | 0.1509 |
0.146 | 2.72 | 300 | 0.1492 |
0.1475 | 2.81 | 310 | 0.1459 |
0.1425 | 2.9 | 320 | 0.1465 |
0.1414 | 2.99 | 330 | 0.1456 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
Model tree for Litzy619/O0428HMA10
Base model
allenai/OLMo-1B