Not-so-bright-AGI-v1
This model is a fine-tuned version of google/gemma-2b on the generator dataset. It achieves the following results on the evaluation set:
- Loss: 2.0548
Model description
More information needed
Intended uses & limitations
More information needed
Training and evaluation data
More information needed
Training Hardware
This model was trained using Intel(R) Data Center GPU Max 1100
Training procedure
Training hyperparameters
The following hyperparameters were used during training:
- learning_rate: 1e-05
- train_batch_size: 4
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.05
- training_steps: 1480
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
2.9165 | 3.2 | 100 | 2.6762 |
2.419 | 6.4 | 200 | 2.3629 |
2.2343 | 9.6 | 300 | 2.2060 |
2.1459 | 12.8 | 400 | 2.1401 |
2.0944 | 16.0 | 500 | 2.1112 |
2.0679 | 19.2 | 600 | 2.0942 |
2.0496 | 22.4 | 700 | 2.0826 |
2.0375 | 25.6 | 800 | 2.0743 |
2.0213 | 28.8 | 900 | 2.0684 |
2.0148 | 32.0 | 1000 | 2.0630 |
2.0048 | 35.2 | 1100 | 2.0593 |
1.9988 | 38.4 | 1200 | 2.0575 |
1.9968 | 41.6 | 1300 | 2.0555 |
1.9908 | 44.8 | 1400 | 2.0548 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.0.1a0+cxx11.abi
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for yuriachermann/Not-so-bright-AGI-v1
Base model
google/gemma-2b