uf-rlced-conifer_tulu-2-7b-dpo-full
This model is a fine-tuned version of allenai/tulu-2-7b on the data/uf_rlced_conifer dataset. It achieves the following results on the evaluation set:
- Loss: 0.3316
- Rewards/chosen: -2.6774
- Rewards/rejected: -5.0456
- Rewards/accuracies: 0.8383
- Rewards/margins: 2.3682
- Logps/rejected: -989.8275
- Logps/chosen: -729.1251
- Logits/rejected: -0.3176
- Logits/chosen: -0.4437
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: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 4
- total_train_batch_size: 256
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 1
Training results
Framework versions
- Transformers 4.44.1
- Pytorch 2.1.2+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1
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