---
library_name: transformers
license: apache-2.0
base_model: tsavage68/IE_M2_1000steps_1e7rate_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: IE_M2_350steps_1e8rate_03beta_cSFTDPO
  results: []
---

<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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# IE_M2_350steps_1e8rate_03beta_cSFTDPO

This model is a fine-tuned version of [tsavage68/IE_M2_1000steps_1e7rate_SFT](https://huggingface.co./tsavage68/IE_M2_1000steps_1e7rate_SFT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6746
- Rewards/chosen: -0.0013
- Rewards/rejected: -0.0404
- Rewards/accuracies: 0.3600
- Rewards/margins: 0.0391
- Logps/rejected: -41.1564
- Logps/chosen: -42.2098
- Logits/rejected: -2.9159
- Logits/chosen: -2.8545

## 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: 350

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6998        | 0.4   | 50   | 0.6949          | 0.0058         | 0.0085           | 0.2050             | -0.0028         | -40.9934       | -42.1863     | -2.9160         | -2.8547       |
| 0.6925        | 0.8   | 100  | 0.6906          | 0.0017         | -0.0041          | 0.2600             | 0.0059          | -41.0355       | -42.1997     | -2.9159         | -2.8546       |
| 0.679         | 1.2   | 150  | 0.6779          | 0.0047         | -0.0273          | 0.3650             | 0.0320          | -41.1127       | -42.1899     | -2.9158         | -2.8546       |
| 0.6715        | 1.6   | 200  | 0.6747          | 0.0020         | -0.0367          | 0.3900             | 0.0387          | -41.1442       | -42.1988     | -2.9156         | -2.8544       |
| 0.6764        | 2.0   | 250  | 0.6736          | -0.0012        | -0.0419          | 0.3850             | 0.0407          | -41.1614       | -42.2094     | -2.9156         | -2.8543       |
| 0.6842        | 2.4   | 300  | 0.6763          | -0.0024        | -0.0380          | 0.3500             | 0.0355          | -41.1483       | -42.2137     | -2.9159         | -2.8545       |
| 0.6712        | 2.8   | 350  | 0.6746          | -0.0013        | -0.0404          | 0.3600             | 0.0391          | -41.1564       | -42.2098     | -2.9159         | -2.8545       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.0.0+cu117
- Datasets 3.0.0
- Tokenizers 0.19.1