Spruteus/brevity_ss-promt_e30

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training_args.bin +3 -0

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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: brevity_ss-promt_e30
+  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. -->
+# brevity_ss-promt_e30
+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: 0.4920
+## 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: 30
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 3.9164        | 0.8   | 2    | 3.1402          |
+| 2.3902        | 2.0   | 5    | 2.6152          |
+| 3.053         | 2.8   | 7    | 2.3220          |
+| 1.7893        | 4.0   | 10   | 1.9873          |
+| 2.3626        | 4.8   | 12   | 1.8054          |
+| 1.3909        | 6.0   | 15   | 1.5493          |
+| 1.8073        | 6.8   | 17   | 1.3868          |
+| 1.0338        | 8.0   | 20   | 1.1445          |
+| 1.2723        | 8.8   | 22   | 0.9763          |
+| 0.6819        | 10.0  | 25   | 0.7926          |
+| 0.8371        | 10.8  | 27   | 0.7085          |
+| 0.4868        | 12.0  | 30   | 0.6329          |
+| 0.6522        | 12.8  | 32   | 0.5975          |
+| 0.4052        | 14.0  | 35   | 0.5653          |
+| 0.5732        | 14.8  | 37   | 0.5482          |
+| 0.3641        | 16.0  | 40   | 0.5303          |
+| 0.5239        | 16.8  | 42   | 0.5213          |
+| 0.3372        | 18.0  | 45   | 0.5101          |
+| 0.4896        | 18.8  | 47   | 0.5041          |
+| 0.3174        | 20.0  | 50   | 0.4974          |
+| 0.4645        | 20.8  | 52   | 0.4949          |
+| 0.3046        | 22.0  | 55   | 0.4929          |
+| 0.4505        | 22.8  | 57   | 0.4923          |
+| 0.2972        | 24.0  | 60   | 0.4920          |
+### Framework versions
+- PEFT 0.10.0
+- Transformers 4.40.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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