O0506TEST4
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: 0.1571
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 |
---|---|---|---|
3.0648 | 0.09 | 10 | 0.3333 |
0.2162 | 0.18 | 20 | 0.1599 |
0.1543 | 0.27 | 30 | 0.1590 |
0.156 | 0.36 | 40 | 0.1528 |
0.1499 | 0.45 | 50 | 0.1497 |
0.1524 | 0.54 | 60 | 0.1513 |
0.1499 | 0.63 | 70 | 0.1484 |
0.1488 | 0.73 | 80 | 0.1535 |
0.1478 | 0.82 | 90 | 0.1494 |
0.1478 | 0.91 | 100 | 0.1522 |
0.1511 | 1.0 | 110 | 0.1511 |
0.1465 | 1.09 | 120 | 0.1502 |
0.1454 | 1.18 | 130 | 0.1467 |
0.615 | 1.27 | 140 | 0.1920 |
5.4883 | 1.36 | 150 | 4.4845 |
1.4468 | 1.45 | 160 | 0.4784 |
0.3848 | 1.54 | 170 | 0.3101 |
0.3022 | 1.63 | 180 | 0.3316 |
0.2716 | 1.72 | 190 | 0.2528 |
0.2376 | 1.81 | 200 | 0.2176 |
0.1874 | 1.9 | 210 | 0.1744 |
0.1817 | 1.99 | 220 | 0.1734 |
0.1673 | 2.08 | 230 | 0.1810 |
0.1646 | 2.18 | 240 | 0.1609 |
0.1565 | 2.27 | 250 | 0.1599 |
0.1545 | 2.36 | 260 | 0.1606 |
0.1527 | 2.45 | 270 | 0.1590 |
0.1537 | 2.54 | 280 | 0.1579 |
0.1502 | 2.63 | 290 | 0.1596 |
0.154 | 2.72 | 300 | 0.1569 |
0.1522 | 2.81 | 310 | 0.1570 |
0.1519 | 2.9 | 320 | 0.1570 |
0.1534 | 2.99 | 330 | 0.1571 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
Model tree for Litzy619/O0506TEST4
Base model
allenai/OLMo-1B