carsenk
/

flippa-v1

PEFT

Safetensors

Generated from Trainer

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carsenk commited on Mar 5

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carsenk/flippa-v1

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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
-<!-- 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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 ---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: TheBloke/Mistral-7B-Instruct-v0.2-GPTQ
+model-index:
+- name: flippa-v1
+  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-v1
+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 the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.8477
+## 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 |
+|:-------------:|:-----:|:----:|:---------------:|
+| 1.2214        | 1.0   | 187  | 1.1960          |
+| 1.0247        | 2.0   | 375  | 1.1154          |
+| 0.9636        | 3.0   | 562  | 1.0554          |
+| 0.9073        | 4.0   | 750  | 1.0037          |
+| 0.8654        | 5.0   | 937  | 0.9583          |
+| 0.8209        | 6.0   | 1125 | 0.9223          |
+| 0.7994        | 7.0   | 1312 | 0.8916          |
+| 0.7553        | 8.0   | 1500 | 0.8685          |
+| 0.7415        | 9.0   | 1687 | 0.8537          |
+| 0.724         | 9.97  | 1870 | 0.8477          |
+### 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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