rishavranaut/Mistral-7B_final_MT

README.md

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+---
+license: apache-2.0
+library_name: peft
+tags:
+- generated_from_trainer
+base_model: mistralai/Mistral-7B-v0.1
+metrics:
+- accuracy
+- precision
+- recall
+model-index:
+- name: Mistral-7B_final_MT
+  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. -->
+
+# Mistral-7B_final_MT
+
+This model is a fine-tuned version of [mistralai/Mistral-7B-v0.1](https://huggingface.co/mistralai/Mistral-7B-v0.1) on the None dataset.
+It achieves the following results on the evaluation set:
+- Loss: 0.7471
+- Accuracy: 0.8
+- Precision: 0.7795
+- Recall: 0.8367
+- F1 score: 0.8071
+
+## 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: 0.0001
+- train_batch_size: 16
+- eval_batch_size: 8
+- seed: 42
+- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
+- lr_scheduler_type: linear
+- num_epochs: 5
+
+### Training results
+
+| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 score |
+|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:--------:|
+| 1.2073        | 0.5   | 200  | 1.0465          | 0.6867   | 0.7857    | 0.5133 | 0.6210   |
+| 0.8334        | 1.0   | 400  | 0.8003          | 0.7317   | 0.7456    | 0.7033 | 0.7238   |
+| 0.4526        | 1.5   | 600  | 0.8224          | 0.7433   | 0.7074    | 0.83   | 0.7638   |
+| 0.4306        | 2.0   | 800  | 0.8715          | 0.7467   | 0.8895    | 0.5633 | 0.6898   |
+| 0.296         | 2.5   | 1000 | 0.6957          | 0.7767   | 0.7441    | 0.8433 | 0.7906   |
+| 0.2864        | 3.0   | 1200 | 0.6663          | 0.7983   | 0.8163    | 0.77   | 0.7925   |
+| 0.1803        | 3.5   | 1400 | 0.6645          | 0.8      | 0.8082    | 0.7867 | 0.7973   |
+| 0.1603        | 4.0   | 1600 | 0.6943          | 0.7833   | 0.7560    | 0.8367 | 0.7943   |
+| 0.0907        | 4.5   | 1800 | 0.7265          | 0.81     | 0.7981    | 0.83   | 0.8137   |
+| 0.0798        | 5.0   | 2000 | 0.7471          | 0.8      | 0.7795    | 0.8367 | 0.8071   |
+
+
+### Framework versions
+
+- PEFT 0.11.1
+- Transformers 4.44.2
+- Pytorch 2.3.0+cu121
+- Datasets 2.19.1
+- Tokenizers 0.19.1

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