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GOLM3
Litzy619/GOLM3
GOLM3 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. --
Access
Public
Updated May 2, 2024
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20.3 GB on disk
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At a glance
- License
- gemma
- Access
- Public
- Created
- May 2, 2024
- Updated
- May 2, 2024
- SHA
- ad07f407
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. -->
GOLM3
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: 0.1033
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 |
|---|---|---|---|
| 1.8196 | 0.09 | 10 | 1.4618 |
| 1.0741 | 0.18 | 20 | 0.5866 |
| 0.3626 | 0.27 | 30 | 0.1793 |
| 0.1587 | 0.36 | 40 | 0.1503 |
| 0.1454 | 0.45 | 50 | 0.1476 |
| 0.1461 | 0.54 | 60 | 0.1476 |
| 0.143 | 0.63 | 70 | 0.1443 |
| 0.1452 | 0.73 | 80 | 0.1424 |
| 0.1345 | 0.82 | 90 | 0.1372 |
| 0.1286 | 0.91 | 100 | 0.1308 |
| 0.131 | 1.0 | 110 | 0.1317 |
| 0.123 | 1.09 | 120 | 0.1265 |
| 0.1161 | 1.18 | 130 | 0.1272 |
| 0.1188 | 1.27 | 140 | 0.1170 |
| 0.1197 | 1.36 | 150 | 0.1149 |
| 0.1139 | 1.45 | 160 | 0.1146 |
| 0.1122 | 1.54 | 170 | 0.1117 |
| 0.1093 | 1.63 | 180 | 0.1098 |
| 0.1093 | 1.72 | 190 | 0.1085 |
| 0.1096 | 1.81 | 200 | 0.1068 |
| 0.1086 | 1.9 | 210 | 0.1064 |
| 0.107 | 1.99 | 220 | 0.1065 |
| 0.0961 | 2.08 | 230 | 0.1069 |
| 0.0946 | 2.18 | 240 | 0.1061 |
| 0.0883 | 2.27 | 250 | 0.1048 |
| 0.0933 | 2.36 | 260 | 0.1039 |
| 0.0904 | 2.45 | 270 | 0.1058 |
| 0.0862 | 2.54 | 280 | 0.1057 |
| 0.0818 | 2.63 | 290 | 0.1047 |
| 0.0852 | 2.72 | 300 | 0.1046 |
| 0.0895 | 2.81 | 310 | 0.1048 |
| 0.0914 | 2.9 | 320 | 0.1044 |
| 0.0909 | 2.99 | 330 | 0.1033 |
Framework versions
- Transformers 4.36.0.dev0
- Pytorch 2.1.2+cu121
- Datasets 2.14.6
- Tokenizers 0.14.1
- License
- gemma
- Created
- May 2, 2024
- Updated
- May 2, 2024