Delete auxiliary_decoder/README.md

auxiliary_decoder/README.md

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----
-library_name: peft
-license: other
-base_model: /cpfs01/shared/ADLab/hug_ckpts/Meta-Llama-3.1-8B-Instruct
-tags:
-- llama-factory
-- lora
-- generated_from_trainer
-model-index:
-- name: 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. -->
-
-# sft
-
-This model is a fine-tuned version of [/cpfs01/shared/ADLab/hug_ckpts/Meta-Llama-3.1-8B-Instruct](https://huggingface.co//cpfs01/shared/ADLab/hug_ckpts/Meta-Llama-3.1-8B-Instruct) on the identity and the chartvlm_all_task datasets.
-It achieves the following results on the evaluation set:
-- Loss: 0.8528
-
-## 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: 0.0001
-- train_batch_size: 1
-- eval_batch_size: 1
-- seed: 42
-- distributed_type: multi-GPU
-- num_devices: 2
-- gradient_accumulation_steps: 8
-- total_train_batch_size: 16
-- total_eval_batch_size: 2
-- 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: 3.0
-
-### Training results
-
-
-
-### Framework versions
-
-- PEFT 0.12.0
-- Transformers 4.46.1
-- Pytorch 2.1.2+cu121
-- Datasets 2.18.0
-- Tokenizers 0.20.3