meditron-7b-dpo-full-wo-live_qa-ep3
This model is a fine-tuned version of epfl-llm/meditron-7b on the HuggingFaceH4/ultrafeedback_binarized dataset. It achieves the following results on the evaluation set:
- Loss: 0.5356
- Rewards/chosen: -0.2871
- Rewards/rejected: -0.7760
- Rewards/accuracies: 0.6923
- Rewards/margins: 0.4889
- Logps/rejected: -1205.3544
- Logps/chosen: -986.1032
- Logits/rejected: -0.8878
- Logits/chosen: -0.8900
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: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- 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: 1
Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|---|---|---|---|---|---|---|---|---|---|---|---|
| 0.583 | 0.49 | 100 | 0.6358 | -0.0392 | -0.1400 | 0.6442 | 0.1009 | -1141.7539 | -961.3083 | -0.8346 | -0.8420 |
| 0.3768 | 0.98 | 200 | 0.5356 | -0.2875 | -0.7751 | 0.7019 | 0.4876 | -1205.2603 | -986.1399 | -0.8883 | -0.8904 |
Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2