gemma7b-summarize-gemini1_5flash-64k
This model is a fine-tuned version of google/gemma-7b on the llama-duo/synth_summarize_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 2.5156
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: 2
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 16
- 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 |
---|---|---|---|
1.2495 | 0.9952 | 104 | 2.6543 |
1.0258 | 2.0 | 209 | 2.5232 |
0.9351 | 2.9952 | 313 | 2.4668 |
0.8914 | 4.0 | 418 | 2.4789 |
0.8487 | 4.9952 | 522 | 2.4752 |
0.8222 | 6.0 | 627 | 2.4928 |
0.7746 | 6.9952 | 731 | 2.4925 |
0.7644 | 8.0 | 836 | 2.5051 |
0.7578 | 8.9952 | 940 | 2.5211 |
0.7589 | 9.9522 | 1040 | 2.5156 |
Framework versions
- PEFT 0.10.0
- Transformers 4.40.0
- Pytorch 2.1.2+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1
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Model tree for llama-duo/gemma7b-summarize-gemini1_5flash-64k
Base model
google/gemma-7b