carsenk
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flippa-v0

PEFT

Safetensors

Generated from Trainer

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carsenk commited on Mar 3

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carsenk/flippa-v0

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 ---
-library_name: transformers
-tags: []
 ---
-# Model Card for Model ID
-<!-- Provide a quick summary of what the model is/does. -->
-## Model Details
-### Model Description
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-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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 ---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
+model-index:
+- name: flippa-v0
+  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. -->
+# flippa-v0
+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: 0.3732
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|
+| 0.7166        | 0.96  | 6    | 0.6408          |
+| 0.633         | 1.92  | 12   | 0.5777          |
+| 0.5688        | 2.88  | 18   | 0.5266          |
+| 0.4524        | 4.0   | 25   | 0.4774          |
+| 0.4781        | 4.96  | 31   | 0.4454          |
+| 0.4538        | 5.92  | 37   | 0.4199          |
+| 0.4233        | 6.88  | 43   | 0.3991          |
+| 0.34          | 8.0   | 50   | 0.3829          |
+| 0.3881        | 8.96  | 56   | 0.3750          |
+| 0.3169        | 9.6   | 60   | 0.3732          |
+### Framework versions
+- PEFT 0.9.0
+- Transformers 4.38.1
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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