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V0507HMA15HV2
Litzy619/V0507HMA15HV2
V0507HMA15HV2 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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Public
Updated May 8, 2024
Parameters
2.9B
6.5 GB on disk
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.safetensors5.9 GB · 91%
Parameter types
How the weights are stored.
F162.8B · 97%
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. -->
V0507HMA15HV2
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: -95.0498
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 |
|---|---|---|---|
| -8.6532 | 0.09 | 10 | -10.3327 |
| -11.8451 | 0.18 | 20 | -14.2014 |
| -17.3537 | 0.27 | 30 | -22.7794 |
| -28.8388 | 0.36 | 40 | -38.5512 |
| -47.1885 | 0.45 | 50 | -59.6364 |
| -67.2573 | 0.54 | 60 | -76.6591 |
| -81.223 | 0.63 | 70 | -86.3414 |
| -87.9651 | 0.73 | 80 | -90.0475 |
| -91.3192 | 0.82 | 90 | -92.4350 |
| -92.7456 | 0.91 | 100 | -93.1825 |
| -93.4032 | 1.0 | 110 | -93.7378 |
| -93.8855 | 1.09 | 120 | -93.9331 |
| -94.0075 | 1.18 | 130 | -93.9987 |
| -94.001 | 1.27 | 140 | -94.3115 |
| -94.3566 | 1.36 | 150 | -94.4505 |
| -94.3346 | 1.45 | 160 | -94.2625 |
| -94.5793 | 1.54 | 170 | -94.3309 |
| -93.2701 | 1.63 | 180 | -93.4388 |
| -94.2829 | 1.72 | 190 | -93.8681 |
| -94.6778 | 1.81 | 200 | -94.7489 |
| -94.5762 | 1.9 | 210 | -94.7745 |
| -94.8427 | 1.99 | 220 | -94.8903 |
| -94.8653 | 2.08 | 230 | -94.8499 |
| -94.9237 | 2.18 | 240 | -94.9720 |
| -95.0027 | 2.27 | 250 | -94.9841 |
| -94.9404 | 2.36 | 260 | -94.8479 |
| -94.9594 | 2.45 | 270 | -95.0076 |
| -95.0772 | 2.54 | 280 | -95.0798 |
| -95.0775 | 2.63 | 290 | -95.0480 |
| -95.0528 | 2.72 | 300 | -95.0415 |
| -95.0652 | 2.81 | 310 | -95.0442 |
| -95.0738 | 2.9 | 320 | -95.0494 |
| -95.0694 | 2.99 | 330 | -95.0498 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.14.1
- License
- mit
- Created
- May 8, 2024
- Updated
- May 8, 2024