Model save

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- trl
+- sft
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+model-index:
+- name: Mistral-7B-Instruct-v0.2-mirage-all-teacher-instruct-mistral-sft
+  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-7B-Instruct-v0.2-mirage-all-teacher-instruct-mistral-sft
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.9628
+
+## 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: 0.0002
+- train_batch_size: 4
+- eval_batch_size: 4
+- seed: 42
+- distributed_type: multi-GPU
+- num_devices: 4
+- total_train_batch_size: 16
+- total_eval_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.1
+- num_epochs: 1
+
+### Training results
+
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 1.3478        | 0.0412 | 200  | 1.2310          |
+| 1.3495        | 0.0824 | 400  | 1.1826          |
+| 1.3753        | 0.1237 | 600  | 1.1557          |
+| 1.3454        | 0.1649 | 800  | 1.1297          |
+| 1.2731        | 0.2061 | 1000 | 1.1071          |
+| 1.3863        | 0.2473 | 1200 | 1.0878          |
+| 1.2567        | 0.2885 | 1400 | 1.0777          |
+| 1.257         | 0.3298 | 1600 | 1.0630          |
+| 1.2129        | 0.3710 | 1800 | 1.0518          |
+| 1.1939        | 0.4122 | 2000 | 1.0405          |
+| 1.2658        | 0.4534 | 2200 | 1.0313          |
+| 1.1718        | 0.4946 | 2400 | 1.0186          |
+| 1.1795        | 0.5359 | 2600 | 1.0102          |
+| 1.1984        | 0.5771 | 2800 | 1.0008          |
+| 1.157         | 0.6183 | 3000 | 0.9930          |
+| 1.1542        | 0.6595 | 3200 | 0.9862          |
+| 1.1648        | 0.7007 | 3400 | 0.9802          |
+| 1.1403        | 0.7420 | 3600 | 0.9750          |
+| 1.1268        | 0.7832 | 3800 | 0.9705          |
+| 1.2122        | 0.8244 | 4000 | 0.9672          |
+| 1.0571        | 0.8656 | 4200 | 0.9649          |
+| 1.0903        | 0.9068 | 4400 | 0.9635          |
+| 1.178         | 0.9481 | 4600 | 0.9629          |
+| 1.1661        | 0.9893 | 4800 | 0.9628          |
+
+
+### Framework versions
+
+- PEFT 0.7.1
+- Transformers 4.41.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.20.0
+- Tokenizers 0.19.1

adapter_model.safetensors

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 size 83946192

all_results.json

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+{
+    "epoch": 1.0,
+    "total_flos": 3.101569705521971e+16,
+    "train_loss": 1.1041986294158312,
+    "train_runtime": 123226.4419,
+    "train_samples": 77623,
+    "train_samples_per_second": 0.63,
+    "train_steps_per_second": 0.039
+}

train_results.json

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+{
+    "epoch": 1.0,
+    "total_flos": 3.101569705521971e+16,
+    "train_loss": 1.1041986294158312,
+    "train_runtime": 123226.4419,
+    "train_samples": 77623,
+    "train_samples_per_second": 0.63,
+    "train_steps_per_second": 0.039
+}