---
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_1000steps_1e5rate_03beta_SFT
  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. -->

# IE_M2_1000steps_1e5rate_03beta_SFT

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: 0.3743
- Rewards/chosen: -0.7553
- Rewards/rejected: -9.7171
- Rewards/accuracies: 0.4600
- Rewards/margins: 8.9618
- Logps/rejected: -73.4121
- Logps/chosen: -44.7232
- Logits/rejected: -2.8541
- Logits/chosen: -2.7894

## 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 |
|:-------------:|:-----:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.4505        | 0.4   | 50   | 0.3743          | -0.6162        | -8.7555          | 0.4600             | 8.1394          | -70.2069       | -44.2594     | -2.8648         | -2.8033       |
| 0.3812        | 0.8   | 100  | 0.3743          | -1.0731        | -9.5409          | 0.4600             | 8.4678          | -72.8247       | -45.7824     | -2.8548         | -2.7905       |
| 0.3119        | 1.2   | 150  | 0.3743          | -0.9410        | -9.5992          | 0.4600             | 8.6582          | -73.0192       | -45.3421     | -2.8541         | -2.7895       |
| 0.3639        | 1.6   | 200  | 0.3743          | -0.7657        | -9.6369          | 0.4600             | 8.8712          | -73.1449       | -44.7578     | -2.8542         | -2.7897       |
| 0.4332        | 2.0   | 250  | 0.3743          | -0.7607        | -9.6350          | 0.4600             | 8.8743          | -73.1384       | -44.7411     | -2.8544         | -2.7898       |
| 0.3986        | 2.4   | 300  | 0.3743          | -0.7630        | -9.6419          | 0.4600             | 8.8789          | -73.1614       | -44.7488     | -2.8543         | -2.7898       |
| 0.3986        | 2.8   | 350  | 0.3743          | -0.7622        | -9.6431          | 0.4600             | 8.8809          | -73.1655       | -44.7462     | -2.8543         | -2.7897       |
| 0.4505        | 3.2   | 400  | 0.3743          | -0.7616        | -9.6621          | 0.4600             | 8.9005          | -73.2290       | -44.7442     | -2.8541         | -2.7895       |
| 0.4505        | 3.6   | 450  | 0.3743          | -0.7588        | -9.6708          | 0.4600             | 8.9120          | -73.2578       | -44.7348     | -2.8543         | -2.7897       |
| 0.4332        | 4.0   | 500  | 0.3743          | -0.7521        | -9.6770          | 0.4600             | 8.9249          | -73.2784       | -44.7124     | -2.8544         | -2.7898       |
| 0.3292        | 4.4   | 550  | 0.3743          | -0.7599        | -9.6954          | 0.4600             | 8.9355          | -73.3399       | -44.7386     | -2.8542         | -2.7896       |
| 0.3639        | 4.8   | 600  | 0.3743          | -0.7497        | -9.6881          | 0.4600             | 8.9385          | -73.3155       | -44.7044     | -2.8543         | -2.7896       |
| 0.4505        | 5.2   | 650  | 0.3743          | -0.7507        | -9.7018          | 0.4600             | 8.9511          | -73.3612       | -44.7080     | -2.8544         | -2.7897       |
| 0.4505        | 5.6   | 700  | 0.3743          | -0.7481        | -9.7110          | 0.4600             | 8.9629          | -73.3918       | -44.6990     | -2.8541         | -2.7895       |
| 0.3639        | 6.0   | 750  | 0.3743          | -0.7516        | -9.7060          | 0.4600             | 8.9544          | -73.3750       | -44.7109     | -2.8541         | -2.7895       |
| 0.2426        | 6.4   | 800  | 0.3743          | -0.7439        | -9.7074          | 0.4600             | 8.9634          | -73.3797       | -44.6853     | -2.8542         | -2.7895       |
| 0.5025        | 6.8   | 850  | 0.3743          | -0.7549        | -9.7166          | 0.4600             | 8.9617          | -73.4105       | -44.7219     | -2.8542         | -2.7895       |
| 0.3119        | 7.2   | 900  | 0.3743          | -0.7562        | -9.7133          | 0.4600             | 8.9571          | -73.3994       | -44.7261     | -2.8541         | -2.7894       |
| 0.3466        | 7.6   | 950  | 0.3743          | -0.7569        | -9.7198          | 0.4600             | 8.9629          | -73.4212       | -44.7285     | -2.8541         | -2.7894       |
| 0.3812        | 8.0   | 1000 | 0.3743          | -0.7553        | -9.7171          | 0.4600             | 8.9618          | -73.4121       | -44.7232     | -2.8541         | -2.7894       |


### Framework versions

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