ggeorge/qlora-mistral-hackatone-yandexq

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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
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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: qlora-mistral-hackatone-yandexq
+  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. -->
+# qlora-mistral-hackatone-yandexq
+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: 1.8327
+## 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: 5e-05
+- train_batch_size: 8
+- eval_batch_size: 8
+- seed: 42
+- gradient_accumulation_steps: 4
+- total_train_batch_size: 32
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- lr_scheduler_warmup_steps: 2
+- num_epochs: 60
+- mixed_precision_training: Native AMP
+### Training results
+| Training Loss | Epoch | Step | Validation Loss |
+|:-------------:|:-----:|:----:|:---------------:|
+| 2.0167        | 1.0   | 1    | 1.9699          |
+| 2.0949        | 2.0   | 2    | 1.9681          |
+| 2.0703        | 3.0   | 3    | 1.9624          |
+| 2.0674        | 4.0   | 4    | 1.9563          |
+| 2.0057        | 5.0   | 5    | 1.9500          |
+| 2.0534        | 6.0   | 6    | 1.9431          |
+| 1.9912        | 7.0   | 7    | 1.9359          |
+| 2.0333        | 8.0   | 8    | 1.9285          |
+| 1.9934        | 9.0   | 9    | 1.9210          |
+| 2.0358        | 10.0  | 10   | 1.9136          |
+| 1.9727        | 11.0  | 11   | 1.9064          |
+| 1.9698        | 12.0  | 12   | 1.8994          |
+| 1.9983        | 13.0  | 13   | 1.8928          |
+| 1.981         | 14.0  | 14   | 1.8865          |
+| 1.9554        | 15.0  | 15   | 1.8807          |
+| 1.935         | 16.0  | 16   | 1.8755          |
+| 1.9203        | 17.0  | 17   | 1.8705          |
+| 1.9371        | 18.0  | 18   | 1.8663          |
+| 1.9184        | 19.0  | 19   | 1.8625          |
+| 1.938         | 20.0  | 20   | 1.8592          |
+| 1.94          | 21.0  | 21   | 1.8565          |
+| 1.9062        | 22.0  | 22   | 1.8542          |
+| 1.9293        | 23.0  | 23   | 1.8520          |
+| 1.9464        | 24.0  | 24   | 1.8503          |
+| 1.9271        | 25.0  | 25   | 1.8488          |
+| 1.8998        | 26.0  | 26   | 1.8473          |
+| 1.9393        | 27.0  | 27   | 1.8461          |
+| 1.9188        | 28.0  | 28   | 1.8449          |
+| 1.9117        | 29.0  | 29   | 1.8438          |
+| 1.8974        | 30.0  | 30   | 1.8428          |
+| 1.9181        | 31.0  | 31   | 1.8418          |
+| 1.9047        | 32.0  | 32   | 1.8409          |
+| 1.8977        | 33.0  | 33   | 1.8400          |
+| 1.8937        | 34.0  | 34   | 1.8392          |
+| 1.8801        | 35.0  | 35   | 1.8385          |
+| 1.9149        | 36.0  | 36   | 1.8377          |
+| 1.9027        | 37.0  | 37   | 1.8372          |
+| 1.9076        | 38.0  | 38   | 1.8366          |
+| 1.8718        | 39.0  | 39   | 1.8362          |
+| 1.9125        | 40.0  | 40   | 1.8357          |
+| 1.8903        | 41.0  | 41   | 1.8353          |
+| 1.8668        | 42.0  | 42   | 1.8350          |
+| 1.8653        | 43.0  | 43   | 1.8347          |
+| 1.9068        | 44.0  | 44   | 1.8345          |
+| 1.869         | 45.0  | 45   | 1.8342          |
+| 1.8844        | 46.0  | 46   | 1.8340          |
+| 1.9001        | 47.0  | 47   | 1.8338          |
+| 1.886         | 48.0  | 48   | 1.8336          |
+| 1.8847        | 49.0  | 49   | 1.8335          |
+| 1.8566        | 50.0  | 50   | 1.8333          |
+| 1.8729        | 51.0  | 51   | 1.8332          |
+| 1.8736        | 52.0  | 52   | 1.8330          |
+| 1.9098        | 53.0  | 53   | 1.8330          |
+| 1.897         | 54.0  | 54   | 1.8329          |
+| 1.8966        | 55.0  | 55   | 1.8328          |
+| 1.8942        | 56.0  | 56   | 1.8328          |
+| 1.871         | 57.0  | 57   | 1.8328          |
+| 1.8434        | 58.0  | 58   | 1.8327          |
+| 1.8743        | 59.0  | 59   | 1.8327          |
+| 1.8472        | 60.0  | 60   | 1.8327          |
+### Framework versions
+- PEFT 0.10.0
+- Transformers 4.38.2
+- Pytorch 2.1.0+cu121
+- Datasets 2.18.0
+- Tokenizers 0.15.2

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