O0508V6
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: 0.0549
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: 80
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
4.9964 | 0.09 | 10 | 2.5378 |
0.9829 | 0.18 | 20 | 0.2281 |
0.1624 | 0.27 | 30 | 0.1521 |
0.1521 | 0.36 | 40 | 0.1504 |
0.1509 | 0.45 | 50 | 0.1504 |
0.152 | 0.54 | 60 | 0.1490 |
0.1502 | 0.63 | 70 | 0.1462 |
0.1406 | 0.73 | 80 | 0.0971 |
0.3907 | 0.82 | 90 | 0.1581 |
0.1531 | 0.91 | 100 | 0.1189 |
1.2928 | 1.0 | 110 | 5.1579 |
1.2381 | 1.09 | 120 | 0.3474 |
0.2465 | 1.18 | 130 | 0.1100 |
0.084 | 1.27 | 140 | 0.0754 |
0.0824 | 1.36 | 150 | 0.0596 |
0.0604 | 1.45 | 160 | 0.0562 |
0.0554 | 1.54 | 170 | 0.0562 |
0.0572 | 1.63 | 180 | 0.0550 |
0.0634 | 1.72 | 190 | 0.0570 |
0.0559 | 1.81 | 200 | 0.0583 |
0.0585 | 1.9 | 210 | 0.0587 |
0.0575 | 1.99 | 220 | 0.0551 |
0.0563 | 2.08 | 230 | 0.0563 |
0.0534 | 2.18 | 240 | 0.0560 |
0.0546 | 2.27 | 250 | 0.0571 |
0.0571 | 2.36 | 260 | 0.0557 |
0.0535 | 2.45 | 270 | 0.0550 |
0.0515 | 2.54 | 280 | 0.0551 |
0.0538 | 2.63 | 290 | 0.0569 |
0.0545 | 2.72 | 300 | 0.0541 |
0.0555 | 2.81 | 310 | 0.0542 |
0.0564 | 2.9 | 320 | 0.0548 |
0.0597 | 2.99 | 330 | 0.0549 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
Model tree for Litzy619/O0508V6
Base model
allenai/OLMo-1B