gemma7b-summarize-gpt4o-2k
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: 7.6472
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 |
---|---|---|---|
47.9246 | 0.8571 | 3 | 15.4847 |
38.5919 | 2.0 | 7 | 12.5499 |
23.0632 | 2.8571 | 10 | 10.1538 |
23.0632 | 4.0 | 14 | 8.4647 |
19.8584 | 4.8571 | 17 | 8.0216 |
19.1062 | 6.0 | 21 | 7.7569 |
19.1062 | 6.8571 | 24 | 7.6779 |
18.5688 | 8.0 | 28 | 7.6438 |
18.5805 | 8.5714 | 30 | 7.6472 |
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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