End of training

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-Instruct-v0.2
+model-index:
+- name: Mistral-Instruct-7B-v0.2-ChatAlpaca
+  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-Instruct-7B-v0.2-ChatAlpaca
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-Instruct-v0.2](https://huggingface.co/mistralai/Mistral-7B-Instruct-v0.2) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8584
+
+## 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: 4e-05
+- train_batch_size: 1
+- eval_batch_size: 2
+- seed: 42
+- gradient_accumulation_steps: 32
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: cosine
+- lr_scheduler_warmup_ratio: 0.05
+- num_epochs: 2
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.99          | 0.2   | 120  | 0.9355          |
+| 0.8793        | 0.39  | 240  | 0.8848          |
+| 0.8671        | 0.59  | 360  | 0.8737          |
+| 0.8662        | 0.78  | 480  | 0.8679          |
+| 0.8627        | 0.98  | 600  | 0.8639          |
+| 0.8426        | 1.18  | 720  | 0.8615          |
+| 0.8574        | 1.37  | 840  | 0.8598          |
+| 0.8473        | 1.57  | 960  | 0.8589          |
+| 0.8528        | 1.76  | 1080 | 0.8585          |
+| 0.852         | 1.96  | 1200 | 0.8584          |
+
+
+### Framework versions
+
+- PEFT 0.7.1
+- Transformers 4.36.2
+- Pytorch 2.1.2+cu121
+- Datasets 2.16.0
+- Tokenizers 0.15.0

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