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V0422MADP6B
Litzy619/V0422MADP6B
V0422MADP6B is a machine learning model from Litzy619. Use it for the machine learning task on the model card, and read the license before you ship it in a product. The card lists the license as mit.
should probably proofread and complete it, then remove this comment. --
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Updated Apr 23, 2024
Parameters
2.9B
6.6 GB on disk
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Repo makeup
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.safetensors6 GB · 90%
Parameter types
How the weights are stored.
F162.8B · 96%
Base models
Model card
From the Hugging Face model README
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
V0422MADP6B
This model is a fine-tuned version of microsoft/phi-2 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.1503
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: 60
- num_epochs: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| 6.0222 | 0.09 | 10 | 2.4466 |
| 4.7074 | 0.18 | 20 | 2.0778 |
| 2.0523 | 0.27 | 30 | 0.9665 |
| 0.5575 | 0.36 | 40 | 0.3469 |
| 0.2173 | 0.45 | 50 | 0.2234 |
| 0.1799 | 0.54 | 60 | 0.2376 |
| 0.1697 | 0.63 | 70 | 0.1977 |
| 0.1625 | 0.73 | 80 | 0.1701 |
| 0.1569 | 0.82 | 90 | 0.1676 |
| 0.1575 | 0.91 | 100 | 0.1651 |
| 0.1632 | 1.0 | 110 | 0.1574 |
| 0.1565 | 1.09 | 120 | 0.1549 |
| 0.1551 | 1.18 | 130 | 0.1690 |
| 0.1574 | 1.27 | 140 | 0.1523 |
| 0.1557 | 1.36 | 150 | 0.1518 |
| 0.1512 | 1.45 | 160 | 0.1524 |
| 0.1615 | 1.54 | 170 | 0.1704 |
| 0.1651 | 1.63 | 180 | 0.1822 |
| 0.1648 | 1.72 | 190 | 0.1652 |
| 0.1567 | 1.81 | 200 | 0.1557 |
| 0.1549 | 1.9 | 210 | 0.1532 |
| 0.152 | 1.99 | 220 | 0.1554 |
| 0.1532 | 2.08 | 230 | 0.1515 |
| 0.1486 | 2.18 | 240 | 0.1529 |
| 0.149 | 2.27 | 250 | 0.1527 |
| 0.1493 | 2.36 | 260 | 0.1515 |
| 0.1507 | 2.45 | 270 | 0.1528 |
| 0.1496 | 2.54 | 280 | 0.1545 |
| 0.1507 | 2.63 | 290 | 0.1516 |
| 0.1481 | 2.72 | 300 | 0.1505 |
| 0.1488 | 2.81 | 310 | 0.1502 |
| 0.1502 | 2.9 | 320 | 0.1502 |
| 0.1522 | 2.99 | 330 | 0.1503 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
- License
- mit
- Created
- Apr 22, 2024
- Updated
- Apr 23, 2024