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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_450steps_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_450steps_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: 0.6907
- Rewards/chosen: -0.0040
- Rewards/rejected: -0.0095
- Rewards/accuracies: 0.4050
- Rewards/margins: 0.0055
- Logps/rejected: -75.7223
- Logps/chosen: -82.8379
- Logits/rejected: -0.7979
- Logits/chosen: -0.7409
## 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: 450
### 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 |
| 0.6904 | 1.2 | 150 | 0.6912 | -0.0066 | -0.0112 | 0.4200 | 0.0046 | -75.7390 | -82.8636 | -0.7971 | -0.7401 |
| 0.6902 | 1.6 | 200 | 0.6897 | -0.0027 | -0.0101 | 0.4250 | 0.0074 | -75.7282 | -82.8243 | -0.7964 | -0.7397 |
| 0.6858 | 2.0 | 250 | 0.6904 | -0.0049 | -0.0110 | 0.3950 | 0.0061 | -75.7372 | -82.8472 | -0.7971 | -0.7403 |
| 0.6903 | 2.4 | 300 | 0.6887 | -0.0076 | -0.0170 | 0.4500 | 0.0094 | -75.7977 | -82.8741 | -0.7971 | -0.7401 |
| 0.6859 | 2.8 | 350 | 0.6898 | -0.0058 | -0.0130 | 0.4150 | 0.0072 | -75.7575 | -82.8558 | -0.7979 | -0.7409 |
| 0.6978 | 3.2 | 400 | 0.6907 | -0.0040 | -0.0095 | 0.4050 | 0.0055 | -75.7223 | -82.8379 | -0.7979 | -0.7409 |
| 0.6889 | 3.6 | 450 | 0.6907 | -0.0040 | -0.0095 | 0.4050 | 0.0055 | -75.7223 | -82.8379 | -0.7979 | -0.7409 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1
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