zephyr-7b-gemma-adaptive_quantile_loss
This model is a fine-tuned version of HuggingFaceH4/zephyr-7b-gemma-sft-v0.1 on the argilla/dpo-mix-7k dataset.
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: 5e-07
- train_batch_size: 2
- eval_batch_size: 4
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 2
Training results
Framework versions
- Transformers 4.40.1
- Pytorch 2.1.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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Model tree for chrlu/zephyr-7b-gemma-adaptive_quantile_loss
Base model
google/gemma-7b
Finetuned
HuggingFaceH4/zephyr-7b-gemma-sft-v0.1