Update README.md

README.md

@@ -2,64 +2,19 @@
 library_name: transformers
 license: other
 base_model: Qwen/Qwen2.5-3B-Instruct
-tags:
-- alignment-handbook
-- generated_from_trainer
-model-index:
-- name: trained_prometheus
-  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. -->
 
-# trained_prometheus
+# M-Prometheus
 
-This model is a fine-tuned version of [Qwen/Qwen2.5-3B-Instruct](https://huggingface.co/Qwen/Qwen2.5-3B-Instruct) on the None dataset.
-It achieves the following results on the evaluation set:
-- Loss: nan
+M-Prometheus is a suite of open LLM judges that can natively evaluate multilingual outputs. They were trained on 480k instances of multilingual direct assessment and pairwise comparison data wiht long-form feedback. 
+They can be prompted in the same way as [Prometheus-2](https://huggingface.co/prometheus-eval/prometheus-7b-v2.0/tree/main).
+Check out our [paper](wip) for more details.
 
-## Model description
+## Citation
 
-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-06
-- train_batch_size: 2
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 8
-- gradient_accumulation_steps: 2
-- total_train_batch_size: 32
-- total_eval_batch_size: 8
-- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
-- lr_scheduler_type: cosine
-- lr_scheduler_warmup_ratio: 0.1
-- num_epochs: 1.0
-
-### Training results
-
-| Training Loss | Epoch  | Step  | Validation Loss |
-|:-------------:|:------:|:-----:|:---------------:|
-| 1.9997        | 1.0000 | 14840 | nan             |
-
-
-### Framework versions
-
-- Transformers 4.46.0
-- Pytorch 2.1.2+cu121
-- Datasets 3.3.1
-- Tokenizers 0.20.3
+```bibtex
+wip
+```