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README.md

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+---
+library_name: transformers
+license: other
+base_model: llava-hf/llava-v1.6-mistral-7b-hf
+tags:
+- llama-factory
+- full
+- generated_from_trainer
+model-index:
+- name: AA_preference_Cherry_0_70
+  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. -->
+
+# AA_preference_Cherry_0_70
+
+This model is a fine-tuned version of [llava-hf/llava-v1.6-mistral-7b-hf](https://huggingface.co/llava-hf/llava-v1.6-mistral-7b-hf) on the AA_preference_Cherry_0_70 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4557
+- Rewards/chosen: 1.5899
+- Rewards/rejected: -1.4032
+- Rewards/accuracies: 0.8198
+- Rewards/margins: 2.9930
+- Logps/rejected: -237.9070
+- Logps/chosen: -288.5520
+- Logits/rejected: -2.0398
+- Logits/chosen: -2.0633
+
+## 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-06
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 8
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 256
+- total_eval_batch_size: 64
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_steps: 10
+- num_epochs: 3.0
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss | Rewards/chosen | Rewards/rejected | Rewards/accuracies | Rewards/margins | Logps/rejected | Logps/chosen | Logits/rejected | Logits/chosen |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.1988        | 1.0554 | 100  | 0.4581          | 1.2441         | -0.7508          | 0.8052             | 1.9949          | -231.3840      | -292.0099    | -2.0274         | -2.0496       |
+| 0.0898        | 2.1108 | 200  | 0.4581          | 1.2188         | -1.4863          | 0.8285             | 2.7050          | -238.7381      | -292.2634    | -2.0389         | -2.0563       |
+
+
+### Framework versions
+
+- Transformers 4.45.2
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.20.3

added_tokens.json

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+  "<pad>": 32001
+}

all_results.json

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+{
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+    "eval_logits/rejected": -2.0397870540618896,
+    "eval_logps/chosen": -288.552001953125,
+    "eval_logps/rejected": -237.90699768066406,
+    "eval_loss": 0.455725759267807,
+    "eval_rewards/accuracies": 0.819767415523529,
+    "eval_rewards/chosen": 1.5898916721343994,
+    "eval_rewards/margins": 2.9930419921875,
+    "eval_rewards/rejected": -1.403150200843811,
+    "eval_runtime": 180.1111,
+    "eval_samples_per_second": 14.93,
+    "eval_steps_per_second": 0.239,
+    "total_flos": 3325131736743936.0,
+    "train_loss": 0.285313792368199,
+    "train_runtime": 10060.2707,
+    "train_samples_per_second": 7.214,
+    "train_steps_per_second": 0.028
+}

checkpoint-100/added_tokens.json

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+  "<pad>": 32001
+}

checkpoint-100/config.json

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+  "architectures": [
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+  ],
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+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": false,
+  "use_image_newline_parameter": true,
+  "vision_config": {
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+    "model_type": "clip_vision_model",
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+    "vocab_size": 32000
+  },
+  "vision_feature_layer": -2,
+  "vision_feature_select_strategy": "default",
+  "vocab_size": 32064
+}

checkpoint-100/generation_config.json

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checkpoint-100/preprocessor_config.json

@@ -0,0 +1,52 @@
+{
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+    "width": 336
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+  "size": {
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