O0507TESTW3
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: 0.1532
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 |
---|---|---|---|
5.3894 | 0.09 | 10 | 2.0100 |
0.6459 | 0.18 | 20 | 0.1973 |
0.1654 | 0.27 | 30 | 0.1585 |
0.1531 | 0.36 | 40 | 0.1511 |
0.1507 | 0.45 | 50 | 0.1494 |
0.1512 | 0.54 | 60 | 0.1485 |
0.1492 | 0.63 | 70 | 0.1490 |
0.1485 | 0.73 | 80 | 0.1502 |
0.1467 | 0.82 | 90 | 0.1483 |
0.1472 | 0.91 | 100 | 0.1497 |
0.15 | 1.0 | 110 | 0.1512 |
0.1444 | 1.09 | 120 | 0.1473 |
0.3286 | 1.18 | 130 | 2.0028 |
4.2528 | 1.27 | 140 | 2.0406 |
2.8791 | 1.36 | 150 | 0.9368 |
0.6013 | 1.45 | 160 | 0.3498 |
0.3067 | 1.54 | 170 | 0.2728 |
0.2472 | 1.63 | 180 | 0.2114 |
0.2014 | 1.72 | 190 | 0.1921 |
0.1816 | 1.81 | 200 | 0.1924 |
0.1673 | 1.9 | 210 | 0.1675 |
0.1651 | 1.99 | 220 | 0.1613 |
0.1584 | 2.08 | 230 | 0.1662 |
0.1565 | 2.18 | 240 | 0.1564 |
0.1504 | 2.27 | 250 | 0.1573 |
0.1518 | 2.36 | 260 | 0.1554 |
0.1489 | 2.45 | 270 | 0.1548 |
0.1499 | 2.54 | 280 | 0.1533 |
0.1477 | 2.63 | 290 | 0.1553 |
0.1519 | 2.72 | 300 | 0.1533 |
0.1499 | 2.81 | 310 | 0.1531 |
0.1496 | 2.9 | 320 | 0.1531 |
0.1512 | 2.99 | 330 | 0.1532 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
Model tree for Litzy619/O0507TESTW3
Base model
allenai/OLMo-1B