Gemma_AAID_mixed_train_final
This model is a fine-tuned version of google/gemma-7b on the AAID_mixed dataset. It achieves the following results on the evaluation set:
- Loss: 0.6593
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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 256
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
3.1586 | 0.0109 | 10 | 0.7969 |
0.6717 | 0.0219 | 20 | 0.7616 |
0.5741 | 0.0328 | 30 | 0.7398 |
0.5809 | 0.0438 | 40 | 0.7745 |
0.5313 | 0.0547 | 50 | 0.7014 |
0.4879 | 0.0656 | 60 | 0.7165 |
0.4665 | 0.0766 | 70 | 0.7070 |
0.4509 | 0.0875 | 80 | 0.7005 |
0.4542 | 0.0984 | 90 | 0.6933 |
0.4188 | 0.1094 | 100 | 0.6599 |
0.4131 | 0.1203 | 110 | 0.6593 |
0.4137 | 0.1313 | 120 | 0.6896 |
0.4087 | 0.1422 | 130 | 0.6930 |
0.3968 | 0.1531 | 140 | 0.6692 |
0.4048 | 0.1641 | 150 | 0.6872 |
0.3953 | 0.1750 | 160 | 0.6939 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.1
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Model tree for Holmeister/Gemma_AAID_mixed_train_final
Base model
google/gemma-7b