gemma7b-summarize-gpt4o-8k
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: 2.8129
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 |
|---|---|---|---|
| 30.8653 | 1.0 | 14 | 10.6638 |
| 18.5328 | 2.0 | 28 | 7.3031 |
| 11.486 | 3.0 | 42 | 6.6280 |
| 2.4959 | 4.0 | 56 | 3.5087 |
| 1.742 | 5.0 | 70 | 3.0216 |
| 1.5971 | 6.0 | 84 | 2.8802 |
| 1.4792 | 7.0 | 98 | 2.8307 |
| 1.4333 | 8.0 | 112 | 2.8081 |
| 1.4129 | 9.0 | 126 | 2.8151 |
| 1.4048 | 10.0 | 140 | 2.8129 |
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