File size: 3,077 Bytes
7b53b4e |
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 |
---
license: llama2
library_name: peft
tags:
- trl
- dpo
- generated_from_trainer
base_model: tokyotech-llm/Swallow-7b-instruct-v0.1
model-index:
- name: train_logs
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. -->
# train_logs
This model is a fine-tuned version of [tokyotech-llm/Swallow-7b-instruct-v0.1](https://huggingface.co/tokyotech-llm/Swallow-7b-instruct-v0.1) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6776
- Rewards/chosen: 0.1044
- Rewards/rejected: 0.0678
- Rewards/accuracies: 0.5983
- Rewards/margins: 0.0365
- Logps/rejected: -195.0584
- Logps/chosen: -198.8751
- Logits/rejected: -1.2872
- Logits/chosen: -1.2718
## 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-06
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- gradient_accumulation_steps: 2
- total_train_batch_size: 8
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 300
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6922 | 0.0351 | 50 | 0.6910 | -0.0173 | -0.0222 | 0.5433 | 0.0050 | -195.9592 | -200.0917 | -1.3115 | -1.2970 |
| 0.6915 | 0.0702 | 100 | 0.6841 | 0.0935 | 0.0721 | 0.5900 | 0.0214 | -195.0160 | -198.9837 | -1.2971 | -1.2823 |
| 0.6819 | 0.1053 | 150 | 0.6792 | 0.1455 | 0.1116 | 0.5900 | 0.0339 | -194.6210 | -198.4638 | -1.2865 | -1.2708 |
| 0.6825 | 0.1404 | 200 | 0.6784 | 0.1161 | 0.0811 | 0.5933 | 0.0350 | -194.9258 | -198.7577 | -1.2871 | -1.2717 |
| 0.6791 | 0.1754 | 250 | 0.6769 | 0.1049 | 0.0670 | 0.6183 | 0.0378 | -195.0665 | -198.8701 | -1.2885 | -1.2730 |
| 0.6826 | 0.2105 | 300 | 0.6776 | 0.1044 | 0.0678 | 0.5983 | 0.0365 | -195.0584 | -198.8751 | -1.2872 | -1.2718 |
### Framework versions
- PEFT 0.11.1
- Transformers 4.41.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1 |