File size: 2,503 Bytes
501e263 f69c191 8af1b21 dfe4fcc 8af1b21 f69c191 501e263 f69c191 501e263 dfe4fcc f69c191 501e263 dfe4fcc 501e263 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 |
---
license: llama2
base_model: epfl-llm/meditron-7b
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- alignment-handbook
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: meditron-7b-dpo-full-wo-kqa_golden-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-kqa_golden-ep3
This model is a fine-tuned version of [epfl-llm/meditron-7b](https://huggingface.co/epfl-llm/meditron-7b) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.4459
- Rewards/chosen: -0.4566
- Rewards/rejected: -1.4012
- Rewards/accuracies: 0.8068
- Rewards/margins: 0.9447
- Logps/rejected: -1444.6896
- Logps/chosen: -859.0582
- Logits/rejected: -0.9203
- Logits/chosen: -0.8310
## 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 | Logits/chosen | Logits/rejected | Logps/chosen | Logps/rejected | Validation Loss | Rewards/accuracies | Rewards/chosen | Rewards/margins | Rewards/rejected |
|:-------------:|:-----:|:----:|:-------------:|:---------------:|:------------:|:--------------:|:---------------:|:------------------:|:--------------:|:---------------:|:----------------:|
| 0.5643 | 0.5 | 100 | -0.6995 | -0.8645 | -818.2397 | -1334.0771 | 0.5890 | 0.7727 | -0.0484 | 0.2467 | -0.2951 |
| 0.3959 | 1.0 | 200 | -0.8310 | -0.9203 | -859.0582 | -1444.6896 | 0.4459 | 0.8068 | -0.4566 | 0.9447 | -1.4012 |
### Framework versions
- Transformers 4.39.0.dev0
- Pytorch 2.1.2
- Datasets 2.14.6
- Tokenizers 0.15.2
|