ayanahye/DocGPT-ft

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@@ -1,199 +1,72 @@
 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
-<!-- Provide a longer summary of what this model is. -->
-This is the model card of a 🤗 transformers model that has been pushed on the Hub. This model card has been automatically generated.
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-## Uses
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 ---
+base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
+library_name: peft
+license: apache-2.0
+tags:
+- generated_from_trainer
+model-index:
+- name: DocGPT-ft
+  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. -->
+# DocGPT-ft
+This model is a fine-tuned version of [TheBloke/Mistral-7B-Instruct-v0.2-GPTQ](https://huggingface.co/TheBloke/Mistral-7B-Instruct-v0.2-GPTQ) on an unknown dataset.
+It achieves the following results on the evaluation set:
+- Loss: 2.3387
+## 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
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 16
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2
+- num_epochs: 10
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch  | Step | Validation Loss |
+|:-------------:|:------:|:----:|:---------------:|
+| 2.4174        | 0.9412 | 12   | 2.2924          |
+| 2.1327        | 1.9608 | 25   | 2.2750          |
+| 2.0864        | 2.9804 | 38   | 2.2745          |
+| 2.0362        | 4.0    | 51   | 2.2761          |
+| 2.1357        | 4.9412 | 63   | 2.2849          |
+| 1.942         | 5.9608 | 76   | 2.2961          |
+| 1.8904        | 6.9804 | 89   | 2.3165          |
+| 1.8585        | 8.0    | 102  | 2.3295          |
+| 1.9923        | 8.9412 | 114  | 2.3390          |
+| 1.6331        | 9.4118 | 120  | 2.3387          |
+### Framework versions
+- PEFT 0.12.0
+- Transformers 4.42.4
+- Pytorch 2.4.0+cu121
+- Datasets 2.21.0
+- Tokenizers 0.19.1

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