sft-gemma-2-2b-ultrafeedback-binarized-20240920-114857
This model is a fine-tuned version of google/gemma-2-2b on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.2499
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: 1.41e-05
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- gradient_accumulation_steps: 128
- total_train_batch_size: 1024
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 3.0
Training results
Training Loss | Epoch | Step | Validation Loss |
---|---|---|---|
1.3539 | 0.3350 | 20 | 1.3197 |
1.3073 | 0.6700 | 40 | 1.2901 |
1.307 | 1.0050 | 60 | 1.2739 |
1.2327 | 1.3400 | 80 | 1.2642 |
1.2515 | 1.6750 | 100 | 1.2567 |
1.2139 | 2.0099 | 120 | 1.2523 |
1.2023 | 2.3449 | 140 | 1.2509 |
1.2031 | 2.6799 | 160 | 1.2499 |
Framework versions
- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.20.0
- Tokenizers 0.19.1
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