O0428HMA12
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: 0.1467
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 |
---|---|---|---|
1.5515 | 0.09 | 10 | 0.1735 |
0.1665 | 0.18 | 20 | 0.1565 |
0.1531 | 0.27 | 30 | 0.1592 |
0.1558 | 0.36 | 40 | 0.1489 |
0.1489 | 0.45 | 50 | 0.1490 |
0.1518 | 0.54 | 60 | 0.1497 |
0.1517 | 0.63 | 70 | 0.1472 |
0.1485 | 0.73 | 80 | 0.1536 |
0.1467 | 0.82 | 90 | 0.1476 |
0.15 | 0.91 | 100 | 0.1674 |
0.1763 | 1.0 | 110 | 0.1856 |
1.0647 | 1.09 | 120 | 8.3962 |
5.0664 | 1.18 | 130 | 1.3023 |
1.0961 | 1.27 | 140 | 0.9335 |
0.6186 | 1.36 | 150 | 0.4091 |
0.41 | 1.45 | 160 | 0.4651 |
0.3489 | 1.54 | 170 | 0.2977 |
0.2826 | 1.63 | 180 | 0.2353 |
0.2238 | 1.72 | 190 | 0.2088 |
0.1962 | 1.81 | 200 | 0.1988 |
0.1893 | 1.9 | 210 | 0.1917 |
0.1879 | 1.99 | 220 | 0.1814 |
0.173 | 2.08 | 230 | 0.1894 |
0.1753 | 2.18 | 240 | 0.1669 |
0.1573 | 2.27 | 250 | 0.1580 |
0.1531 | 2.36 | 260 | 0.1547 |
0.1429 | 2.45 | 270 | 0.1496 |
0.1464 | 2.54 | 280 | 0.1471 |
0.1387 | 2.63 | 290 | 0.1482 |
0.1414 | 2.72 | 300 | 0.1460 |
0.1477 | 2.81 | 310 | 0.1461 |
0.1425 | 2.9 | 320 | 0.1466 |
0.1399 | 2.99 | 330 | 0.1467 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
Model tree for Litzy619/O0428HMA12
Base model
allenai/OLMo-1B