gemma7b-summarize-gpt4o-1k
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: 8.6199
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 |
---|---|---|---|
45.5656 | 1.0 | 2 | 16.5046 |
45.5656 | 2.0 | 4 | 14.2000 |
35.6654 | 3.0 | 6 | 12.9944 |
35.6654 | 4.0 | 8 | 11.5695 |
22.2461 | 5.0 | 10 | 10.3065 |
22.2461 | 6.0 | 12 | 9.3645 |
22.2461 | 7.0 | 14 | 8.9071 |
19.7508 | 8.0 | 16 | 8.6934 |
19.7508 | 9.0 | 18 | 8.6287 |
19.172 | 10.0 | 20 | 8.6199 |
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-1k
Base model
google/gemma-7b