gemma7b-summarize-gpt4o-128k
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: 2.4869
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 |
|---|---|---|---|
| 1.1594 | 0.9977 | 219 | 2.6195 |
| 1.0276 | 2.0 | 439 | 2.4670 |
| 0.9492 | 2.9977 | 658 | 2.4451 |
| 0.8751 | 4.0 | 878 | 2.4359 |
| 0.8477 | 4.9977 | 1097 | 2.4390 |
| 0.809 | 6.0 | 1317 | 2.4546 |
| 0.7918 | 6.9977 | 1536 | 2.4592 |
| 0.7847 | 8.0 | 1756 | 2.4783 |
| 0.7808 | 8.9977 | 1975 | 2.4889 |
| 0.7794 | 9.9772 | 2190 | 2.4869 |
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-gpt4o-128k
Base model
google/gemma-7b