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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_random_0_50
+  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_random_0_50
+
+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_random_0_50 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.6024
+- Rewards/chosen: 1.2815
+- Rewards/rejected: -0.9739
+- Rewards/accuracies: 0.7917
+- Rewards/margins: 2.2554
+- Logps/rejected: -218.7351
+- Logps/chosen: -248.4081
+- Logits/rejected: -2.2174
+- Logits/chosen: -2.2436
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.5788        | 0.7463 | 50   | 0.5886          | 1.3112         | -0.0126          | 0.7667             | 1.3238          | -209.1226      | -248.1118    | -2.3816         | -2.3948       |
+| 0.2623        | 1.4925 | 100  | 0.6057          | 1.5827         | -0.4999          | 0.8042             | 2.0826          | -213.9953      | -245.3966    | -2.2436         | -2.2727       |
+| 0.1176        | 2.2388 | 150  | 0.5923          | 1.4688         | -0.7137          | 0.7875             | 2.1825          | -216.1334      | -246.5355    | -2.2235         | -2.2485       |
+| 0.1387        | 2.9851 | 200  | 0.6027          | 1.2815         | -0.9739          | 0.7875             | 2.2554          | -218.7351      | -248.4080    | -2.2176         | -2.2437       |
+
+
+### 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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+{
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+  "<pad>": 32001
+}

all_results.json

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+{
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+    "eval_logits/chosen": -2.2436294555664062,
+    "eval_logits/rejected": -2.2173898220062256,
+    "eval_logps/chosen": -248.40806579589844,
+    "eval_logps/rejected": -218.735107421875,
+    "eval_loss": 0.6023992896080017,
+    "eval_rewards/accuracies": 0.7916666865348816,
+    "eval_rewards/chosen": 1.2815405130386353,
+    "eval_rewards/margins": 2.2554075717926025,
+    "eval_rewards/rejected": -0.9738670587539673,
+    "eval_runtime": 125.4397,
+    "eval_samples_per_second": 15.147,
+    "eval_steps_per_second": 0.239,
+    "total_flos": 2369906314051584.0,
+    "train_loss": 0.32727647339230154,
+    "train_runtime": 7356.5112,
+    "train_samples_per_second": 6.971,
+    "train_steps_per_second": 0.027
+}

checkpoint-100/added_tokens.json

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+  "<pad>": 32001
+}

checkpoint-100/config.json

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+  "use_cache": false,
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+  "vision_config": {
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+    "model_type": "clip_vision_model",
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+    "vocab_size": 32000
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+  "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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