gemma7b-summarize-gpt4o-32k
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: 2.5602
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 |
---|---|---|---|
3.5798 | 1.0 | 55 | 4.0590 |
1.346 | 2.0 | 110 | 2.6944 |
1.1944 | 3.0 | 165 | 2.6027 |
1.1119 | 4.0 | 220 | 2.5779 |
1.0741 | 5.0 | 275 | 2.5495 |
1.0435 | 6.0 | 330 | 2.5501 |
1.0191 | 7.0 | 385 | 2.5536 |
0.9965 | 8.0 | 440 | 2.5604 |
0.9986 | 9.0 | 495 | 2.5597 |
0.9948 | 10.0 | 550 | 2.5602 |
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-32k
Base model
google/gemma-7b