|
--- |
|
license: llama3 |
|
base_model: tsavage68/MedQA_L3_1000steps_1e6rate_SFT |
|
tags: |
|
- trl |
|
- dpo |
|
- generated_from_trainer |
|
model-index: |
|
- name: MedQA_L3_250steps_1e7rate_05beta_CSFTDPO |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# MedQA_L3_250steps_1e7rate_05beta_CSFTDPO |
|
|
|
This model is a fine-tuned version of [tsavage68/MedQA_L3_1000steps_1e6rate_SFT](https://huggingface.co/tsavage68/MedQA_L3_1000steps_1e6rate_SFT) on an unknown dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.6492 |
|
- Rewards/chosen: 0.3403 |
|
- Rewards/rejected: 0.2334 |
|
- Rewards/accuracies: 0.6857 |
|
- Rewards/margins: 0.1070 |
|
- Logps/rejected: -33.3881 |
|
- Logps/chosen: -30.6478 |
|
- Logits/rejected: -0.7314 |
|
- Logits/chosen: -0.7307 |
|
|
|
## 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-07 |
|
- 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 | |
|
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:| |
|
| 0.6857 | 0.0489 | 50 | 0.6947 | -0.0249 | -0.0232 | 0.4879 | -0.0018 | -33.9011 | -31.3784 | -0.7318 | -0.7312 | |
|
| 0.6799 | 0.0977 | 100 | 0.6734 | 0.3881 | 0.3450 | 0.6681 | 0.0432 | -33.1649 | -30.5522 | -0.7330 | -0.7323 | |
|
| 0.6286 | 0.1466 | 150 | 0.6528 | 0.4844 | 0.3866 | 0.6813 | 0.0978 | -33.0816 | -30.3598 | -0.7312 | -0.7306 | |
|
| 0.6183 | 0.1954 | 200 | 0.6449 | 0.3270 | 0.2107 | 0.7143 | 0.1163 | -33.4334 | -30.6745 | -0.7312 | -0.7305 | |
|
| 0.6593 | 0.2443 | 250 | 0.6492 | 0.3403 | 0.2334 | 0.6857 | 0.1070 | -33.3881 | -30.6478 | -0.7314 | -0.7307 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.1 |
|
- Pytorch 2.0.0+cu117 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
