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---
base_model: sanchit-gandhi/distil-zephyr-1.5b-ssft-ultrachat
tags:
- alignment-handbook
- trl
- dpo
- generated_from_trainer
- trl
- dpo
- generated_from_trainer
datasets:
- HuggingFaceH4/ultrafeedback_binarized
model-index:
- name: sanchit-gandhi/distil-zephyr-1.5b-ssft-ultrachat
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. -->
# sanchit-gandhi/distil-zephyr-1.5b-ssft-ultrachat
This model is a fine-tuned version of [sanchit-gandhi/distil-zephyr-1.5b-ssft-ultrachat](https://huggingface.co/sanchit-gandhi/distil-zephyr-1.5b-ssft-ultrachat) on the HuggingFaceH4/ultrafeedback_binarized dataset.
It achieves the following results on the evaluation set:
- Loss: 0.6412
- Rewards/chosen: -0.1044
- Rewards/rejected: -0.2494
- Rewards/accuracies: 0.6445
- Rewards/margins: 0.1450
- Logps/rejected: -429.4582
- Logps/chosen: -433.6304
- Logits/rejected: -3.2047
- Logits/chosen: -3.2544
## 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-07
- train_batch_size: 8
- eval_batch_size: 8
- seed: 42
- distributed_type: multi-GPU
- num_devices: 8
- gradient_accumulation_steps: 2
- total_train_batch_size: 128
- 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: 1
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
| 0.6795 | 0.2092 | 100 | 0.6759 | 0.0017 | -0.0328 | 0.6289 | 0.0345 | -407.8037 | -423.0197 | -3.2565 | -3.3136 |
| 0.6584 | 0.4184 | 200 | 0.6534 | -0.0666 | -0.1617 | 0.6445 | 0.0951 | -420.6952 | -429.8561 | -3.2240 | -3.2768 |
| 0.6494 | 0.6276 | 300 | 0.6438 | -0.1077 | -0.2410 | 0.6211 | 0.1333 | -428.6237 | -433.9640 | -3.2050 | -3.2553 |
| 0.6428 | 0.8368 | 400 | 0.6415 | -0.1001 | -0.2437 | 0.6211 | 0.1436 | -428.8884 | -433.2000 | -3.2046 | -3.2543 |
### Framework versions
- Transformers 4.40.1
- Pytorch 2.2.2+cu121
- Datasets 2.19.0
- Tokenizers 0.19.1
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