---
library_name: transformers
license: apache-2.0
base_model: tsavage68/Na_M2_1000steps_1e7_SFT
tags:
- trl
- dpo
- generated_from_trainer
model-index:
- name: Na_M2_1000steps_1e8rate_05beta_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. -->

# Na_M2_1000steps_1e8rate_05beta_cSFTDPO

This model is a fine-tuned version of [tsavage68/Na_M2_1000steps_1e7_SFT](https://huggingface.co/tsavage68/Na_M2_1000steps_1e7_SFT) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3285
- Rewards/chosen: 0.2983
- Rewards/rejected: -0.6864
- Rewards/accuracies: 1.0
- Rewards/margins: 0.9847
- Logps/rejected: -81.2962
- Logps/chosen: -47.5358
- Logits/rejected: -2.5349
- Logits/chosen: -2.5474

## 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: 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 |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6915        | 0.2667 | 50   | 0.6994          | 0.0060         | 0.0118           | 0.5400             | -0.0058         | -79.8998       | -48.1204     | -2.5353         | -2.5479       |
| 0.6635        | 0.5333 | 100  | 0.6459          | 0.0371         | -0.0697          | 0.7100             | 0.1068          | -80.0629       | -48.0583     | -2.5354         | -2.5480       |
| 0.5585        | 0.8    | 150  | 0.5484          | 0.1041         | -0.2242          | 0.9400             | 0.3283          | -80.3718       | -47.9241     | -2.5344         | -2.5470       |
| 0.5041        | 1.0667 | 200  | 0.4568          | 0.1548         | -0.4106          | 1.0                | 0.5654          | -80.7446       | -47.8228     | -2.5349         | -2.5475       |
| 0.4012        | 1.3333 | 250  | 0.3983          | 0.2253         | -0.5152          | 1.0                | 0.7405          | -80.9538       | -47.6818     | -2.5354         | -2.5479       |
| 0.3304        | 1.6    | 300  | 0.3692          | 0.2306         | -0.6109          | 1.0                | 0.8415          | -81.1452       | -47.6712     | -2.5346         | -2.5472       |
| 0.3396        | 1.8667 | 350  | 0.3524          | 0.2373         | -0.6582          | 1.0                | 0.8955          | -81.2397       | -47.6578     | -2.5349         | -2.5474       |
| 0.3311        | 2.1333 | 400  | 0.3304          | 0.2656         | -0.7177          | 1.0                | 0.9834          | -81.3589       | -47.6011     | -2.5350         | -2.5475       |
| 0.3099        | 2.4    | 450  | 0.3378          | 0.2807         | -0.6665          | 1.0                | 0.9472          | -81.2563       | -47.5710     | -2.5361         | -2.5486       |
| 0.3384        | 2.6667 | 500  | 0.3271          | 0.2743         | -0.7151          | 1.0                | 0.9894          | -81.3535       | -47.5838     | -2.5349         | -2.5474       |
| 0.3381        | 2.9333 | 550  | 0.3284          | 0.2854         | -0.7005          | 1.0                | 0.9859          | -81.3243       | -47.5616     | -2.5347         | -2.5472       |
| 0.3328        | 3.2    | 600  | 0.3217          | 0.2963         | -0.7183          | 1.0                | 1.0146          | -81.3600       | -47.5398     | -2.5349         | -2.5474       |
| 0.3162        | 3.4667 | 650  | 0.3252          | 0.3046         | -0.6916          | 1.0                | 0.9962          | -81.3066       | -47.5232     | -2.5358         | -2.5483       |
| 0.2907        | 3.7333 | 700  | 0.3331          | 0.3002         | -0.6711          | 1.0                | 0.9713          | -81.2656       | -47.5319     | -2.5350         | -2.5475       |
| 0.3052        | 4.0    | 750  | 0.3279          | 0.2998         | -0.6877          | 1.0                | 0.9875          | -81.2988       | -47.5328     | -2.5350         | -2.5474       |
| 0.3264        | 4.2667 | 800  | 0.3285          | 0.2983         | -0.6864          | 1.0                | 0.9847          | -81.2962       | -47.5358     | -2.5349         | -2.5474       |
| 0.3196        | 4.5333 | 850  | 0.3285          | 0.2983         | -0.6864          | 1.0                | 0.9847          | -81.2962       | -47.5358     | -2.5349         | -2.5474       |
| 0.2962        | 4.8    | 900  | 0.3285          | 0.2983         | -0.6864          | 1.0                | 0.9847          | -81.2962       | -47.5358     | -2.5349         | -2.5474       |
| 0.3115        | 5.0667 | 950  | 0.3285          | 0.2983         | -0.6864          | 1.0                | 0.9847          | -81.2962       | -47.5358     | -2.5349         | -2.5474       |
| 0.3285        | 5.3333 | 1000 | 0.3285          | 0.2983         | -0.6864          | 1.0                | 0.9847          | -81.2962       | -47.5358     | -2.5349         | -2.5474       |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.0+cu121
- Datasets 2.21.0
- Tokenizers 0.19.1