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---
library_name: transformers
base_model: data/OpenELM-1_1B-SFT-2
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: OpenELM-1_1B-DPO-full-2
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. -->
# OpenELM-1_1B-DPO-full-2
This model is a fine-tuned version of [data/OpenELM-1_1B-SFT-2](https://huggingface.co/data/OpenELM-1_1B-SFT-2) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7945
- Rewards/chosen: -8.3125
- Rewards/rejected: -10.4375
- Rewards/accuracies: 0.7324
- Rewards/margins: 2.1406
- Logps/rejected: -1336.0
- Logps/chosen: -1144.0
- Logits/rejected: 5.5
- Logits/chosen: 3.5938
## 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: 5e-05
- train_batch_size: 8
- eval_batch_size: 16
- seed: 42
- distributed_type: multi-GPU
- num_devices: 4
- gradient_accumulation_steps: 2
- total_train_batch_size: 64
- total_eval_batch_size: 64
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: cosine
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6007 | 0.1047 | 100 | 0.6140 | -1.2344 | -1.5781 | 0.6562 | 0.3418 | -444.0 | -438.0 | -8.5 | -8.8125 |
| 0.591 | 0.2093 | 200 | 0.6025 | -1.9297 | -2.4688 | 0.6895 | 0.5312 | -532.0 | -508.0 | -6.9375 | -7.5312 |
| 0.6351 | 0.3140 | 300 | 0.5962 | -2.2344 | -2.6875 | 0.6875 | 0.4512 | -556.0 | -540.0 | -4.9062 | -5.7812 |
| 0.6031 | 0.4186 | 400 | 0.5900 | -1.7109 | -2.2812 | 0.6875 | 0.5625 | -512.0 | -486.0 | -6.25 | -7.2188 |
| 0.5813 | 0.5233 | 500 | 0.5824 | -2.25 | -2.8125 | 0.7051 | 0.5547 | -568.0 | -540.0 | -3.6406 | -4.8125 |
| 0.5376 | 0.6279 | 600 | 0.5624 | -2.625 | -3.3281 | 0.7012 | 0.7109 | -620.0 | -576.0 | 2.4219 | 0.9258 |
| 0.5582 | 0.7326 | 700 | 0.5655 | -3.2812 | -4.0938 | 0.7051 | 0.8008 | -696.0 | -644.0 | -0.3281 | -1.7891 |
| 0.5437 | 0.8373 | 800 | 0.5704 | -2.8281 | -3.4375 | 0.6992 | 0.6172 | -632.0 | -596.0 | -1.6719 | -3.1719 |
| 0.567 | 0.9419 | 900 | 0.5633 | -3.1406 | -3.9062 | 0.7227 | 0.7539 | -676.0 | -628.0 | -1.0781 | -2.4219 |
| 0.223 | 1.0466 | 1000 | 0.5835 | -4.1562 | -5.25 | 0.7461 | 1.0859 | -812.0 | -732.0 | 3.375 | 1.7734 |
| 0.1774 | 1.1512 | 1100 | 0.6000 | -4.8438 | -5.9688 | 0.7227 | 1.1328 | -884.0 | -800.0 | 2.8906 | 0.9844 |
| 0.1868 | 1.2559 | 1200 | 0.5954 | -4.9062 | -6.0625 | 0.7188 | 1.1484 | -892.0 | -804.0 | 3.5 | 1.9609 |
| 0.1871 | 1.3605 | 1300 | 0.6086 | -5.3438 | -6.5 | 0.7324 | 1.1562 | -932.0 | -848.0 | 3.1719 | 1.3281 |
| 0.1651 | 1.4652 | 1400 | 0.5995 | -5.375 | -6.4688 | 0.7090 | 1.0938 | -932.0 | -852.0 | 2.9375 | 1.0625 |
| 0.1557 | 1.5699 | 1500 | 0.6073 | -5.3125 | -6.5938 | 0.7012 | 1.2656 | -944.0 | -848.0 | 1.9219 | -0.1582 |
| 0.2145 | 1.6745 | 1600 | 0.6256 | -5.1875 | -6.4688 | 0.7031 | 1.2656 | -932.0 | -832.0 | 3.0469 | 0.9570 |
| 0.1666 | 1.7792 | 1700 | 0.6223 | -5.5312 | -6.8438 | 0.7246 | 1.3047 | -972.0 | -868.0 | 3.8906 | 1.7969 |
| 0.164 | 1.8838 | 1800 | 0.6084 | -4.6875 | -5.9375 | 0.7383 | 1.2266 | -880.0 | -784.0 | 2.6562 | 0.5117 |
| 0.1552 | 1.9885 | 1900 | 0.6211 | -5.4375 | -6.7812 | 0.7363 | 1.3359 | -964.0 | -856.0 | 2.5469 | 0.4004 |
| 0.0204 | 2.0931 | 2000 | 0.6830 | -6.4062 | -8.0 | 0.7383 | 1.6328 | -1088.0 | -952.0 | 4.1562 | 2.1719 |
| 0.0205 | 2.1978 | 2100 | 0.8096 | -9.0 | -11.125 | 0.7168 | 2.1094 | -1400.0 | -1216.0 | 5.4375 | 3.5469 |
| 0.0228 | 2.3025 | 2200 | 0.8077 | -8.625 | -10.8125 | 0.7305 | 2.1562 | -1368.0 | -1176.0 | 5.25 | 3.3281 |
| 0.0148 | 2.4071 | 2300 | 0.7832 | -8.1875 | -10.1875 | 0.7227 | 2.0469 | -1304.0 | -1128.0 | 5.25 | 3.3906 |
| 0.0202 | 2.5118 | 2400 | 0.7835 | -8.1875 | -10.25 | 0.7344 | 2.0781 | -1312.0 | -1136.0 | 5.3125 | 3.375 |
| 0.01 | 2.6164 | 2500 | 0.7940 | -8.1875 | -10.3125 | 0.7363 | 2.1094 | -1320.0 | -1136.0 | 5.4688 | 3.5312 |
| 0.0153 | 2.7211 | 2600 | 0.8036 | -8.5625 | -10.75 | 0.7324 | 2.1719 | -1360.0 | -1168.0 | 5.625 | 3.75 |
| 0.0205 | 2.8257 | 2700 | 0.7961 | -8.375 | -10.5 | 0.7344 | 2.1562 | -1336.0 | -1152.0 | 5.5312 | 3.6406 |
| 0.0184 | 2.9304 | 2800 | 0.7947 | -8.3125 | -10.5 | 0.7324 | 2.1562 | -1336.0 | -1144.0 | 5.5 | 3.5938 |
### Framework versions
- Transformers 4.44.2
- Pytorch 2.3.0
- Datasets 2.21.0
- Tokenizers 0.19.1
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