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---
library_name: transformers
license: llama3
base_model: tsavage68/IE_L3_1000steps_1e6rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: IE_L3_1000steps_1e8rate_01beta_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. -->
# IE_L3_1000steps_1e8rate_01beta_cSFTDPO
This model is a fine-tuned version of [tsavage68/IE_L3_1000steps_1e6rate_SFT](https://huggingface.co/tsavage68/IE_L3_1000steps_1e6rate_SFT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6897
- Rewards/chosen: -0.0098
- Rewards/rejected: -0.0175
- Rewards/accuracies: 0.4200
- Rewards/margins: 0.0078
- Logps/rejected: -75.8027
- Logps/chosen: -82.8953
- Logits/rejected: -0.7964
- Logits/chosen: -0.7394
## 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-08
- 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: 1000
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6965 | 0.4 | 50 | 0.6929 | -0.0030 | -0.0041 | 0.3700 | 0.0011 | -75.6681 | -82.8275 | -0.7963 | -0.7392 |
| 0.6948 | 0.8 | 100 | 0.6908 | -0.0022 | -0.0074 | 0.4250 | 0.0052 | -75.7008 | -82.8198 | -0.7961 | -0.7393 |
| 0.6921 | 1.2 | 150 | 0.6946 | -0.0077 | -0.0055 | 0.375 | -0.0022 | -75.6824 | -82.8750 | -0.7972 | -0.7399 |
| 0.6892 | 1.6 | 200 | 0.6941 | -0.0042 | -0.0030 | 0.3950 | -0.0012 | -75.6573 | -82.8394 | -0.7973 | -0.7404 |
| 0.6937 | 2.0 | 250 | 0.6911 | -0.0037 | -0.0083 | 0.4000 | 0.0046 | -75.7098 | -82.8345 | -0.7973 | -0.7405 |
| 0.6933 | 2.4 | 300 | 0.6899 | -0.0039 | -0.0110 | 0.4300 | 0.0071 | -75.7376 | -82.8367 | -0.7965 | -0.7395 |
| 0.6915 | 2.8 | 350 | 0.6870 | -0.0023 | -0.0151 | 0.4700 | 0.0128 | -75.7783 | -82.8204 | -0.7964 | -0.7393 |
| 0.6933 | 3.2 | 400 | 0.6894 | -0.0069 | -0.0151 | 0.4100 | 0.0082 | -75.7783 | -82.8666 | -0.7958 | -0.7387 |
| 0.6981 | 3.6 | 450 | 0.6882 | 0.0006 | -0.0100 | 0.4350 | 0.0106 | -75.7275 | -82.7918 | -0.7968 | -0.7398 |
| 0.6904 | 4.0 | 500 | 0.6896 | -0.0001 | -0.0078 | 0.4050 | 0.0077 | -75.7054 | -82.7989 | -0.7958 | -0.7391 |
| 0.6964 | 4.4 | 550 | 0.6867 | -0.0021 | -0.0157 | 0.4400 | 0.0136 | -75.7838 | -82.8187 | -0.7965 | -0.7396 |
| 0.6939 | 4.8 | 600 | 0.6902 | 0.0015 | -0.0050 | 0.4000 | 0.0065 | -75.6771 | -82.7829 | -0.7968 | -0.7398 |
| 0.6963 | 5.2 | 650 | 0.6892 | -0.0069 | -0.0155 | 0.4200 | 0.0085 | -75.7818 | -82.8672 | -0.7964 | -0.7394 |
| 0.6951 | 5.6 | 700 | 0.6873 | -0.0025 | -0.0149 | 0.4650 | 0.0124 | -75.7766 | -82.8228 | -0.7963 | -0.7389 |
| 0.6855 | 6.0 | 750 | 0.6876 | -0.0066 | -0.0183 | 0.4550 | 0.0118 | -75.8105 | -82.8633 | -0.7965 | -0.7394 |
| 0.6873 | 6.4 | 800 | 0.6877 | -0.0072 | -0.0189 | 0.4550 | 0.0117 | -75.8165 | -82.8698 | -0.7964 | -0.7394 |
| 0.6848 | 6.8 | 850 | 0.6898 | -0.0098 | -0.0173 | 0.4100 | 0.0075 | -75.8003 | -82.8958 | -0.7964 | -0.7394 |
| 0.6983 | 7.2 | 900 | 0.6897 | -0.0098 | -0.0175 | 0.4200 | 0.0078 | -75.8027 | -82.8953 | -0.7964 | -0.7394 |
| 0.6859 | 7.6 | 950 | 0.6897 | -0.0098 | -0.0175 | 0.4200 | 0.0078 | -75.8027 | -82.8953 | -0.7964 | -0.7394 |
| 0.6888 | 8.0 | 1000 | 0.6897 | -0.0098 | -0.0175 | 0.4200 | 0.0078 | -75.8027 | -82.8953 | -0.7964 | -0.7394 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1
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