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---
license: llama2
base_model: epfl-llm/meditron-7b
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: meditron-7b-dpo-full-wo-live_qa-ep3
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. -->
# meditron-7b-dpo-full-wo-live_qa-ep3
This model is a fine-tuned version of [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.5356
- Rewards/chosen: -0.2875
- Rewards/rejected: -0.7751
- Rewards/accuracies: 0.7019
- Rewards/margins: 0.4876
- Logps/rejected: -1205.2603
- Logps/chosen: -986.1399
- Logits/rejected: -0.8883
- Logits/chosen: -0.8904
## 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
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