gemma2b-closedqa-gpt4o-100k
This model is a fine-tuned version of google/gemma-2b on the llama-duo/synth_closed_qa_dataset_dedup dataset. It achieves the following results on the evaluation set:
- Loss: 2.6811
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 3
- gradient_accumulation_steps: 2
- total_train_batch_size: 48
- total_eval_batch_size: 24
- 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 |
---|---|---|---|
1.0659 | 0.9983 | 287 | 2.2446 |
0.9881 | 2.0 | 575 | 2.2538 |
0.9259 | 2.9983 | 862 | 2.2906 |
0.8772 | 4.0 | 1150 | 2.3648 |
0.8436 | 4.9983 | 1437 | 2.4373 |
0.7905 | 6.0 | 1725 | 2.5194 |
0.757 | 6.9983 | 2012 | 2.6101 |
0.7274 | 8.0 | 2300 | 2.6532 |
0.721 | 8.9983 | 2587 | 2.6792 |
0.7142 | 9.9826 | 2870 | 2.6811 |
Framework versions
- PEFT 0.11.1
- Transformers 4.41.2
- Pytorch 2.2.2+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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Base model
google/gemma-2b