gemma-7b-sft-qlora-no-robots15
This model is a fine-tuned version of google/gemma-7b on the chansung/no_robots_only_coding dataset. It achieves the following results on the evaluation set:
- Loss: 1.2808
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: 0.0002
- train_batch_size: 2
- eval_batch_size: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 16
- total_eval_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
21.9058 | 0.91 | 5 | 7.6562 |
13.5645 | 2.0 | 11 | 6.6359 |
10.2613 | 2.91 | 16 | 6.0754 |
9.903 | 4.0 | 22 | 3.1116 |
4.594 | 4.91 | 27 | 1.6371 |
1.6122 | 6.0 | 33 | 1.4160 |
1.3971 | 6.91 | 38 | 1.3411 |
1.2757 | 8.0 | 44 | 1.3074 |
1.1233 | 8.91 | 49 | 1.2756 |
0.9741 | 10.0 | 55 | 1.2736 |
0.9266 | 10.91 | 60 | 1.2791 |
0.8584 | 12.0 | 66 | 1.2753 |
0.8714 | 12.91 | 71 | 1.2842 |
0.8421 | 13.64 | 75 | 1.2808 |
Framework versions
- PEFT 0.7.1
- Transformers 4.39.3
- Pytorch 2.2.2+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for chansung/gemma-7b-sft-qlora-no-robots15
Base model
google/gemma-7b