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---
license: apache-2.0
base_model: alignment-handbook/zephyr-7b-sft-full
tags:
- alignment-handbook
- ndcg
- trl
- generated_from_trainer
- trl
- ndcg
- generated_from_trainer
datasets:
- yangzhao02/ListUltraFeedback
model-index:
- name: mistral-7b-base-dpo-list_mle-listsize_8-beta_0.05-batchsize_128
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. -->
[<img src="https://raw.githubusercontent.com/wandb/assets/main/wandb-github-badge-28.svg" alt="Visualize in Weights & Biases" width="200" height="32"/>](https://wandb.ai/zhaoyang1/huggingface/runs/xug99v0l)
# mistral-7b-base-dpo-list_mle-listsize_8-beta_0.05-batchsize_128
This model is a fine-tuned version of [alignment-handbook/zephyr-7b-sft-full](https://huggingface.co/alignment-handbook/zephyr-7b-sft-full) on the yangzhao02/ListUltraFeedback dataset.
It achieves the following results on the evaluation set:
- Loss: 6.7425
- Logps: -316.4365
- Logits: -2.1289
## 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: 1
- eval_batch_size: 1
- seed: 42
- distributed_type: multi-GPU
- num_devices: 16
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- total_eval_batch_size: 16
- 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
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Logits | Logps | Validation Loss |
|:-------------:|:------:|:----:|:-------:|:---------:|:---------------:|
| 6.8406 | 0.5343 | 250 | -2.2186 | -311.0428 | 6.9513 |
### Framework versions
- Transformers 4.42.0
- Pytorch 2.3.0+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
|