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gemma-3-4b-it-arkey_emails-qlora
xaviergillard/gemma-3-4b-it-arkey_emails-qlora
gemma-3-4b-it-arkey_emails-qlora is a machine learning model from xaviergillard. Use it for the machine learning task on the model card, and read the license before you ship it in a product. It is set up for peft. The card lists the license as gemma.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Library
- peft
- License
- gemma
- Access
- Public
- Created
- May 8, 2025
- Updated
- May 12, 2025
- SHA
- 7936236a
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. -->
gemma-3-4b-it-arkey_emails-qlora
This model is a fine-tuned version of google/gemma-3-4b-it on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.5329
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: 5e-05
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- gradient_accumulation_steps: 64
- total_train_batch_size: 128
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 50
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 5 | 3.9168 |
| No log | 2.0 | 10 | 3.5567 |
| No log | 3.0 | 15 | 3.2439 |
| No log | 4.0 | 20 | 3.0028 |
| No log | 5.0 | 25 | 2.8257 |
| No log | 6.0 | 30 | 2.6974 |
| No log | 7.0 | 35 | 2.6045 |
| No log | 8.0 | 40 | 2.5319 |
| No log | 9.0 | 45 | 2.4673 |
| No log | 10.0 | 50 | 2.4065 |
| No log | 11.0 | 55 | 2.3477 |
| No log | 12.0 | 60 | 2.2918 |
| No log | 13.0 | 65 | 2.2379 |
| No log | 14.0 | 70 | 2.1864 |
| No log | 15.0 | 75 | 2.1368 |
| No log | 16.0 | 80 | 2.0882 |
| No log | 17.0 | 85 | 2.0429 |
| No log | 18.0 | 90 | 1.9999 |
| No log | 19.0 | 95 | 1.9580 |
| No log | 20.0 | 100 | 1.9175 |
| No log | 21.0 | 105 | 1.8778 |
| No log | 22.0 | 110 | 1.8372 |
| No log | 23.0 | 115 | 1.7964 |
| No log | 24.0 | 120 | 1.7642 |
| No log | 25.0 | 125 | 1.7354 |
| No log | 26.0 | 130 | 1.7083 |
| No log | 27.0 | 135 | 1.6831 |
| No log | 28.0 | 140 | 1.6598 |
| No log | 29.0 | 145 | 1.6386 |
| No log | 30.0 | 150 | 1.6197 |
| No log | 31.0 | 155 | 1.6029 |
| No log | 32.0 | 160 | 1.5880 |
| No log | 33.0 | 165 | 1.5750 |
| No log | 34.0 | 170 | 1.5638 |
| No log | 35.0 | 175 | 1.5543 |
| No log | 36.0 | 180 | 1.5466 |
| No log | 37.0 | 185 | 1.5407 |
| No log | 38.0 | 190 | 1.5365 |
| No log | 39.0 | 195 | 1.5339 |
| No log | 40.0 | 200 | 1.5329 |
Framework versions
- PEFT 0.15.2
- Transformers 4.51.3
- Pytorch 2.1.2
- Datasets 3.5.1
- Tokenizers 0.21.1
- Library
- peft
- License
- gemma
- Created
- May 8, 2025
- Updated
- May 12, 2025