---
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
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# 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