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gemma2-seq-classifier
richardsalas/gemma2-seq-classifier
gemma2-seq-classifier is a machine learning model from richardsalas. 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 5, 2025
- Updated
- May 5, 2025
- SHA
- aa682aa5
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. -->
gemma2-seq-classifier
This model is a fine-tuned version of google/gemma-2-2b-it on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.3055
- Accuracy: 0.9615
- F1 Weighted: 0.9615
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: 2e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 16
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 7
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 Weighted |
|---|---|---|---|---|---|
| 3.9281 | 1.0 | 9 | 1.6771 | 0.2692 | 0.2055 |
| 1.1348 | 2.0 | 18 | 0.7641 | 0.7308 | 0.6936 |
| 0.4717 | 3.0 | 27 | 0.4725 | 0.8462 | 0.8474 |
| 0.338 | 4.0 | 36 | 0.4282 | 0.8462 | 0.8419 |
| 0.1643 | 5.0 | 45 | 0.3055 | 0.9615 | 0.9615 |
| 0.1278 | 6.0 | 54 | 0.3215 | 0.9231 | 0.9219 |
| 0.0692 | 7.0 | 63 | 0.3393 | 0.9615 | 0.9615 |
Framework versions
- PEFT 0.15.2
- Transformers 4.50.0.dev0
- Pytorch 2.6.0
- Datasets 3.5.1
- Tokenizers 0.21.1
- Library
- peft
- License
- gemma
- Created
- May 5, 2025
- Updated
- May 5, 2025