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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: UTI2_M2_75steps_1e7rate_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. -->
# UTI2_M2_75steps_1e7rate_01beta_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: 0.1276
- Rewards/chosen: 0.0336
- Rewards/rejected: -4.2997
- Rewards/accuracies: 0.8800
- Rewards/margins: 4.3333
- Logps/rejected: -82.3535
- Logps/chosen: -19.5858
- Logits/rejected: -2.5678
- Logits/chosen: -2.5670
## 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-07
- 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: 75
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6904 | 0.3333 | 25 | 0.6532 | 0.0086 | -0.0741 | 0.8500 | 0.0827 | -40.0972 | -19.8359 | -2.6814 | -2.6788 |
| 0.4057 | 0.6667 | 50 | 0.3414 | 0.0792 | -0.9298 | 0.8800 | 1.0089 | -48.6537 | -19.1297 | -2.6601 | -2.6575 |
| 0.0995 | 1.0 | 75 | 0.1276 | 0.0336 | -4.2997 | 0.8800 | 4.3333 | -82.3535 | -19.5858 | -2.5678 | -2.5670 |
### Framework versions
- Transformers 4.41.2
- Pytorch 2.0.0+cu117
- Datasets 2.19.2
- Tokenizers 0.19.1
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