gemma7bit-lora-sql
This model is a fine-tuned version of google/gemma-7b on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 0.4155
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: 1399
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 500
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
16.1657 | 0.06 | 20 | 13.6485 |
7.8281 | 0.13 | 40 | 0.7808 |
0.6243 | 0.19 | 60 | 0.5270 |
0.5179 | 0.25 | 80 | 0.4859 |
0.4908 | 0.32 | 100 | 0.4754 |
0.4752 | 0.38 | 120 | 0.4600 |
0.4877 | 0.45 | 140 | 0.4584 |
0.4626 | 0.51 | 160 | 0.4560 |
0.4569 | 0.57 | 180 | 0.4428 |
0.4504 | 0.64 | 200 | 0.4354 |
0.4432 | 0.7 | 220 | 0.4348 |
0.4395 | 0.76 | 240 | 0.4317 |
0.4338 | 0.83 | 260 | 0.4256 |
0.4308 | 0.89 | 280 | 0.4260 |
0.4283 | 0.95 | 300 | 0.4210 |
0.4146 | 1.02 | 320 | 0.4225 |
0.3848 | 1.08 | 340 | 0.4186 |
0.3812 | 1.14 | 360 | 0.4185 |
0.38 | 1.21 | 380 | 0.4200 |
0.3795 | 1.27 | 400 | 0.4171 |
0.3766 | 1.34 | 420 | 0.4174 |
0.3772 | 1.4 | 440 | 0.4136 |
0.3777 | 1.46 | 460 | 0.4148 |
0.379 | 1.53 | 480 | 0.4155 |
Framework versions
- PEFT 0.9.0
- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
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Model tree for jjovalle99/gemma7bit-lora-sql
Base model
google/gemma-7b