Mixtral-7B-AIPI-finetune/checkpoint-500

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-v0.1
+model-index:
+- name: mistral-journal-finetune-aipi
+  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. -->
+
+# mistral-journal-finetune-aipi
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.7849
+
+## 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: 2.5e-05
+- train_batch_size: 2
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 1
+- training_steps: 500
+- mixed_precision_training: Native AMP
+
+### Training results
+
+| Training Loss | Epoch   | Step | Validation Loss |
+|:-------------:|:-------:|:----:|:---------------:|
+| 1.3541        | 0.6757  | 25   | 1.4800          |
+| 0.8644        | 1.3514  | 50   | 1.4804          |
+| 0.8449        | 2.0270  | 75   | 1.5426          |
+| 0.5501        | 2.7027  | 100  | 1.6733          |
+| 0.2691        | 3.3784  | 125  | 1.8077          |
+| 0.2187        | 4.0541  | 150  | 1.9603          |
+| 0.1408        | 4.7297  | 175  | 2.0132          |
+| 0.0892        | 5.4054  | 200  | 2.2048          |
+| 0.0891        | 6.0811  | 225  | 2.2487          |
+| 0.0633        | 6.7568  | 250  | 2.2303          |
+| 0.0516        | 7.4324  | 275  | 2.2637          |
+| 0.0479        | 8.1081  | 300  | 2.2366          |
+| 0.0486        | 8.7838  | 325  | 2.3266          |
+| 0.0435        | 9.4595  | 350  | 2.5567          |
+| 0.0389        | 10.1351 | 375  | 2.6020          |
+| 0.04          | 10.8108 | 400  | 2.7252          |
+| 0.0341        | 11.4865 | 425  | 2.6801          |
+| 0.0357        | 12.1622 | 450  | 2.7342          |
+| 0.0363        | 12.8378 | 475  | 2.7706          |
+| 0.0342        | 13.5135 | 500  | 2.7849          |
+
+
+### Framework versions
+
+- PEFT 0.10.1.dev0
+- Transformers 4.40.0.dev0
+- Pytorch 2.2.1+cu121
+- Datasets 2.18.0
+- Tokenizers 0.19.0

adapter_config.json

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+{
+  "alpha_pattern": {},
+  "auto_mapping": null,
+  "base_model_name_or_path": "mistralai/Mistral-7B-v0.1",
+  "bias": "none",
+  "fan_in_fan_out": false,
+  "inference_mode": true,
+  "init_lora_weights": true,
+  "layer_replication": null,
+  "layers_pattern": null,
+  "layers_to_transform": null,
+  "loftq_config": {},
+  "lora_alpha": 64,
+  "lora_dropout": 0.05,
+  "megatron_config": null,
+  "megatron_core": "megatron.core",
+  "modules_to_save": null,
+  "peft_type": "LORA",
+  "r": 32,
+  "rank_pattern": {},
+  "revision": null,
+  "target_modules": [
+    "up_proj",
+    "k_proj",
+    "v_proj",
+    "q_proj",
+    "down_proj",
+    "gate_proj",
+    "o_proj",
+    "lm_head"
+  ],
+  "task_type": "CAUSAL_LM",
+  "use_dora": false,
+  "use_rslora": false
+}

adapter_model.safetensors

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training_args.bin

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