metadata
license: llama3
base_model: meta-llama/Meta-Llama-3-8B-Instruct
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: MedQA_L3_250steps_1e6rate_05beat_CSFTDPO
results: []
MedQA_L3_250steps_1e6rate_05beat_CSFTDPO
This model is a fine-tuned version of meta-llama/Meta-Llama-3-8B-Instruct on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.5035
- Rewards/chosen: -0.9245
- Rewards/rejected: -2.5465
- Rewards/accuracies: 0.7626
- Rewards/margins: 1.6220
- Logps/rejected: -26.4095
- Logps/chosen: -20.0716
- Logits/rejected: -0.9727
- Logits/chosen: -0.9715
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: 1e-06
- train_batch_size: 2
- eval_batch_size: 1
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 4
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_steps: 100
- training_steps: 250
Training results
Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
---|---|---|---|---|---|---|---|---|---|---|---|
0.7075 | 0.0489 | 50 | 0.6367 | 0.2363 | 0.0705 | 0.6571 | 0.1658 | -21.1755 | -17.7501 | -0.9379 | -0.9373 |
0.6451 | 0.0977 | 100 | 0.6114 | -0.8886 | -1.7629 | 0.6923 | 0.8743 | -24.8423 | -19.9998 | -0.9999 | -0.9992 |
0.7372 | 0.1466 | 150 | 0.5770 | -1.9159 | -3.2984 | 0.7253 | 1.3825 | -27.9133 | -22.0544 | -0.9880 | -0.9871 |
0.4401 | 0.1954 | 200 | 0.5109 | -0.9476 | -2.5465 | 0.7516 | 1.5989 | -26.4095 | -20.1178 | -0.9750 | -0.9738 |
0.6774 | 0.2443 | 250 | 0.5035 | -0.9245 | -2.5465 | 0.7626 | 1.6220 | -26.4095 | -20.0716 | -0.9727 | -0.9715 |
Framework versions
- Transformers 4.41.0
- Pytorch 2.0.0+cu117
- Datasets 2.19.1
- Tokenizers 0.19.1