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G0514HMA25H
Litzy619/G0514HMA25H
G0514HMA25H 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 gemma.
should probably proofread and complete it, then remove this comment. --
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Public
Updated May 15, 2024
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At a glance
- License
- gemma
- Access
- Public
- Created
- May 14, 2024
- Updated
- May 15, 2024
- SHA
- aa6a6f18
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. -->
G0514HMA25H
This model is a fine-tuned version of google/gemma-2b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: -17.9022
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 |
|---|---|---|---|
| 0.8009 | 0.09 | 10 | -0.2103 |
| -1.0796 | 0.18 | 20 | -2.5087 |
| -3.9095 | 0.27 | 30 | -5.8273 |
| -7.2606 | 0.36 | 40 | -9.1358 |
| -10.3742 | 0.45 | 50 | -12.0428 |
| -13.0694 | 0.54 | 60 | -14.4715 |
| -15.2349 | 0.63 | 70 | -16.0930 |
| -16.5217 | 0.73 | 80 | -16.9969 |
| -17.1884 | 0.82 | 90 | -17.3938 |
| -17.4707 | 0.91 | 100 | -17.5554 |
| -17.5868 | 1.0 | 110 | -17.6315 |
| -17.6564 | 1.09 | 120 | -17.6735 |
| -17.688 | 1.18 | 130 | -17.7003 |
| -17.709 | 1.27 | 140 | -17.7200 |
| -17.7262 | 1.36 | 150 | -17.7362 |
| -17.7401 | 1.45 | 160 | -17.7476 |
| -17.7557 | 1.54 | 170 | -17.7664 |
| -17.7777 | 1.63 | 180 | -17.7896 |
| -17.7948 | 1.72 | 190 | -17.8078 |
| -17.8232 | 1.81 | 200 | -17.8337 |
| -17.8393 | 1.9 | 210 | -17.8518 |
| -17.8561 | 1.99 | 220 | -17.8679 |
| -17.8673 | 2.08 | 230 | -17.8730 |
| -17.8748 | 2.18 | 240 | -17.8887 |
| -17.8874 | 2.27 | 250 | -17.8931 |
| -17.8901 | 2.36 | 260 | -17.8972 |
| -17.8918 | 2.45 | 270 | -17.8974 |
| -17.8952 | 2.54 | 280 | -17.9002 |
| -17.898 | 2.63 | 290 | -17.9012 |
| -17.8994 | 2.72 | 300 | -17.9019 |
| -17.8999 | 2.81 | 310 | -17.9020 |
| -17.9012 | 2.9 | 320 | -17.9022 |
| -17.8998 | 2.99 | 330 | -17.9022 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.0
- License
- gemma
- Created
- May 14, 2024
- Updated
- May 15, 2024