The genne/nhn_dpo_v3_T3Q-ko-solar-dpo-v3.0_DPO model is a fine-tuned version of the chihoonlee10/T3Q-ko-solar-dpo-v3.0 model. It was trained using a learning rate of 5e-07 and a cosine learning rate scheduler over 1 epoch. This model is optimized for tasks related to its base model, though specific differentiators and intended uses require further information.
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Model Overview
This model, genne/nhn_dpo_v3_T3Q-ko-solar-dpo-v3.0_DPO, is a fine-tuned iteration of the chihoonlee10/T3Q-ko-solar-dpo-v3.0 base model. While specific details regarding its primary differentiators, intended uses, and the dataset used for fine-tuning are not provided in the current documentation, the training process involved specific hyperparameters.
Training Details
The fine-tuning was conducted with the following key parameters:
- Learning Rate: 5e-07
- Optimizer: Adam with betas=(0.9, 0.999) and epsilon=1e-08
- Batch Size: A
train_batch_sizeof 1 andeval_batch_sizeof 8, leading to atotal_train_batch_sizeandtotal_eval_batch_sizeof 48 due togradient_accumulation_stepsof 8 across 6 devices. - Epochs: The model was trained for 1 epoch.
- Scheduler: A cosine learning rate scheduler with a warmup ratio of 0.1 was utilized.
Framework Versions
The training environment used:
- Transformers 4.36.2
- Pytorch 2.0.1+cu117
- Datasets 2.16.1
- Tokenizers 0.15.1
Further information is needed to fully understand the model's specific capabilities and optimal use cases.
Top 3 parameter combinations used by Featherless users for this model. Click a tab to see each config.