gemma7b-summarize-gpt4o-4k
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: 6.0322
Model description
More information needed
Intended uses & limitations
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Training and evaluation data
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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 |
|---|---|---|---|
| 44.3098 | 1.0 | 7 | 13.7204 |
| 25.7366 | 2.0 | 14 | 8.6916 |
| 19.0375 | 3.0 | 21 | 7.6308 |
| 18.2973 | 4.0 | 28 | 7.1198 |
| 14.8387 | 5.0 | 35 | 6.8470 |
| 12.5684 | 6.0 | 42 | 6.8495 |
| 9.6308 | 7.0 | 49 | 6.6799 |
| 5.7187 | 8.0 | 56 | 6.0818 |
| 4.8487 | 9.0 | 63 | 6.0318 |
| 4.4303 | 10.0 | 70 | 6.0322 |
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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Base model
google/gemma-7b