Model save

README.md

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+---
+license: llama3
+base_model: TIGER-Lab/Mantis-8B-siglip-llama3
+tags:
+- generated_from_trainer
+model-index:
+- name: mma_mantis_from_tuned_293k-seq_len_8192-lr_1e-5-gl_bs_128-ep_1
+  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://salesforceairesearch.wandb.io/jianguozhang/Mantis/runs/as3arldf)
+# mma_mantis_from_tuned_293k-seq_len_8192-lr_1e-5-gl_bs_128-ep_1
+
+This model is a fine-tuned version of [TIGER-Lab/Mantis-8B-siglip-llama3](https://huggingface.co/TIGER-Lab/Mantis-8B-siglip-llama3) on an unknown dataset.
+
+## 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: 1e-05
+- train_batch_size: 1
+- eval_batch_size: 1
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 16
+- total_train_batch_size: 128
+- total_eval_batch_size: 8
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.03
+- num_epochs: 1.0
+
+### Training results
+
+
+
+### Framework versions
+
+- Transformers 4.43.0
+- Pytorch 2.4.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.1

generation_config.json

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+{
+  "_from_model_config": true,
+  "bos_token_id": 128000,
+  "eos_token_id": 128001,
+  "pad_token_id": 128257,
+  "transformers_version": "4.43.0"
+}