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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_40
+  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_40
+
+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_40 dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.5902
+- Rewards/chosen: 1.1361
+- Rewards/rejected: -0.8413
+- Rewards/accuracies: 0.7552
+- Rewards/margins: 1.9774
+- Logps/rejected: -247.4370
+- Logps/chosen: -255.4082
+- Logits/rejected: -2.3629
+- Logits/chosen: -2.3927
+
+## 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 |
+|:-------------:|:------:|:----:|:---------------:|:--------------:|:----------------:|:------------------:|:---------------:|:--------------:|:------------:|:---------------:|:-------------:|
+| 0.5323        | 0.9346 | 50   | 0.5824          | 0.9205         | -0.3508          | 0.7396             | 1.2713          | -242.5313      | -257.5635    | -2.3512         | -2.3802       |
+| 0.2441        | 1.8692 | 100  | 0.5841          | 1.0720         | -0.7661          | 0.7708             | 1.8380          | -246.6841      | -256.0490    | -2.3634         | -2.3957       |
+| 0.1203        | 2.8037 | 150  | 0.5899          | 1.1373         | -0.8378          | 0.7760             | 1.9751          | -247.4010      | -255.3957    | -2.3639         | -2.3938       |
+
+
+### 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": -2.3927104473114014,
+    "eval_logits/rejected": -2.3628900051116943,
+    "eval_logps/chosen": -255.4082489013672,
+    "eval_logps/rejected": -247.4369659423828,
+    "eval_loss": 0.5902177691459656,
+    "eval_rewards/accuracies": 0.7552083134651184,
+    "eval_rewards/chosen": 1.1360557079315186,
+    "eval_rewards/margins": 1.9774025678634644,
+    "eval_rewards/rejected": -0.8413467407226562,
+    "eval_runtime": 100.4193,
+    "eval_samples_per_second": 15.137,
+    "eval_steps_per_second": 0.239,
+    "total_flos": 1874604243025920.0,
+    "train_loss": 0.33037466410570926,
+    "train_runtime": 5730.1243,
+    "train_samples_per_second": 7.16,
+    "train_steps_per_second": 0.028
+}

checkpoint-100/added_tokens.json

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+{
+  "<image>": 32000,
+  "<pad>": 32001
+}

checkpoint-100/config.json

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+  ],
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+    "model_type": "mistral",
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+  "tie_word_embeddings": false,
+  "torch_dtype": "bfloat16",
+  "transformers_version": "4.45.2",
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+  "use_image_newline_parameter": true,
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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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+  "eos_token_id": 2,
+  "transformers_version": "4.45.2"
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@@ -0,0 +1,52 @@
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special_tokens_map.json

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+  "extra_special_tokens": {
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train_results.json

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trainer_log.jsonl

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