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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_80
+  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_80
+
+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_80 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.4646
+- Rewards/chosen: 1.3854
+- Rewards/rejected: -2.0318
+- Rewards/accuracies: 0.8495
+- Rewards/margins: 3.4173
+- Logps/rejected: -243.1421
+- Logps/chosen: -276.4326
+- Logits/rejected: -2.0370
+- Logits/chosen: -2.0845
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.5761        | 0.9259 | 100  | 0.4648          | 1.1012         | -1.0931          | 0.8061             | 2.1944          | -233.7547      | -279.2745    | -2.1461         | -2.1677       |
+| 0.2547        | 1.8519 | 200  | 0.4681          | 1.5677         | -1.4567          | 0.8367             | 3.0244          | -237.3907      | -274.6099    | -2.0097         | -2.0551       |
+| 0.1018        | 2.7778 | 300  | 0.4645          | 1.3964         | -2.0290          | 0.8495             | 3.4254          | -243.1136      | -276.3229    | -2.0408         | -2.0880       |
+
+
+### 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": -2.0369815826416016,
+    "eval_logps/chosen": -276.4326477050781,
+    "eval_logps/rejected": -243.14205932617188,
+    "eval_loss": 0.46458277106285095,
+    "eval_rewards/accuracies": 0.8494898080825806,
+    "eval_rewards/chosen": 1.3854371309280396,
+    "eval_rewards/margins": 3.4172792434692383,
+    "eval_rewards/rejected": -2.0318422317504883,
+    "eval_runtime": 206.292,
+    "eval_samples_per_second": 14.896,
+    "eval_steps_per_second": 0.238,
+    "total_flos": 3820433807769600.0,
+    "train_loss": 0.29292676165515996,
+    "train_runtime": 11688.2747,
+    "train_samples_per_second": 7.096,
+    "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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+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
+  "use_cache": false,
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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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+  "transformers_version": "4.45.2"
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@@ -0,0 +1,52 @@
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