gemma7-closedqa-gpt4o-100k
This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_closed_qa_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 5.0765
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: 4
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 24
- total_eval_batch_size: 12
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 10
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
0.8445 | 0.9991 | 574 | 2.1107 |
0.784 | 2.0 | 1149 | 2.2301 |
0.6545 | 2.9991 | 1723 | 2.4329 |
0.5693 | 4.0 | 2298 | 2.7030 |
0.4555 | 4.9991 | 2872 | 3.1445 |
0.3504 | 6.0 | 3447 | 3.7197 |
0.2672 | 6.9991 | 4021 | 4.3078 |
0.2167 | 8.0 | 4596 | 4.8456 |
0.2037 | 8.9991 | 5170 | 5.0561 |
0.1899 | 9.9913 | 5740 | 5.0765 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
google/gemma-7b