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---
license: apache-2.0
base_model: tsavage68/UTI_M2_1000steps_1e7rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: UTI_M2_1000steps_1e5rate_03beta_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. -->
# UTI_M2_1000steps_1e5rate_03beta_CSFTDPO
This model is a fine-tuned version of [tsavage68/UTI_M2_1000steps_1e7rate_SFT](https://huggingface.co/tsavage68/UTI_M2_1000steps_1e7rate_SFT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6931
- Rewards/chosen: 0.0
- Rewards/rejected: 0.0
- Rewards/accuracies: 0.0
- Rewards/margins: 0.0
- Logps/rejected: 0.0
- Logps/chosen: 0.0
- Logits/rejected: -2.7147
- Logits/chosen: -2.7147
## 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-05
- 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 |
|:-------------:|:-------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6931 | 0.3333 | 25 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 0.6667 | 50 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 1.0 | 75 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 1.3333 | 100 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 1.6667 | 125 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 2.0 | 150 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 2.3333 | 175 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 2.6667 | 200 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 3.0 | 225 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 3.3333 | 250 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 3.6667 | 275 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 4.0 | 300 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 4.3333 | 325 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 4.6667 | 350 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 5.0 | 375 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 5.3333 | 400 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 5.6667 | 425 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 6.0 | 450 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 6.3333 | 475 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 6.6667 | 500 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 7.0 | 525 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 7.3333 | 550 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 7.6667 | 575 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 8.0 | 600 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 8.3333 | 625 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 8.6667 | 650 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 9.0 | 675 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 9.3333 | 700 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 9.6667 | 725 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 10.0 | 750 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 10.3333 | 775 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 10.6667 | 800 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 11.0 | 825 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 11.3333 | 850 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 11.6667 | 875 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 12.0 | 900 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 12.3333 | 925 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 12.6667 | 950 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 13.0 | 975 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
| 0.6931 | 13.3333 | 1000 | 0.6931 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 | -2.7147 | -2.7147 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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