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mohit19906/mistral-7b-Ins-IntentAndEntity
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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: working
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. -->
# working
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: 1.6079
## 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: 6
- eval_batch_size: 6
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 24
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 2
- num_epochs: 50
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| 4.3979 | 0.96 | 6 | 3.3561 |
| 2.837 | 1.92 | 12 | 2.2656 |
| 1.9777 | 2.88 | 18 | 1.7212 |
| 1.3641 | 4.0 | 25 | 1.4591 |
| 1.3384 | 4.96 | 31 | 1.2543 |
| 1.1314 | 5.92 | 37 | 1.1326 |
| 0.9904 | 6.88 | 43 | 1.0707 |
| 0.7908 | 8.0 | 50 | 1.0784 |
| 0.8779 | 8.96 | 56 | 1.0891 |
| 0.8415 | 9.92 | 62 | 1.1026 |
| 0.8044 | 10.88 | 68 | 1.1326 |
| 0.6611 | 12.0 | 75 | 1.1425 |
| 0.7385 | 12.96 | 81 | 1.2161 |
| 0.7071 | 13.92 | 87 | 1.2182 |
| 0.6841 | 14.88 | 93 | 1.2865 |
| 0.5671 | 16.0 | 100 | 1.3092 |
| 0.6442 | 16.96 | 106 | 1.3813 |
| 0.629 | 17.92 | 112 | 1.3295 |
| 0.6197 | 18.88 | 118 | 1.4387 |
| 0.522 | 20.0 | 125 | 1.3785 |
| 0.6013 | 20.96 | 131 | 1.4355 |
| 0.5928 | 21.92 | 137 | 1.4321 |
| 0.5901 | 22.88 | 143 | 1.4711 |
| 0.5015 | 24.0 | 150 | 1.4916 |
| 0.5817 | 24.96 | 156 | 1.5001 |
| 0.578 | 25.92 | 162 | 1.5077 |
| 0.5758 | 26.88 | 168 | 1.5173 |
| 0.4914 | 28.0 | 175 | 1.4935 |
| 0.5732 | 28.96 | 181 | 1.5161 |
| 0.5715 | 29.92 | 187 | 1.5131 |
| 0.5696 | 30.88 | 193 | 1.5400 |
| 0.4861 | 32.0 | 200 | 1.5338 |
| 0.5666 | 32.96 | 206 | 1.5474 |
| 0.5643 | 33.92 | 212 | 1.5519 |
| 0.5643 | 34.88 | 218 | 1.5710 |
| 0.4819 | 36.0 | 225 | 1.5723 |
| 0.5607 | 36.96 | 231 | 1.5749 |
| 0.5609 | 37.92 | 237 | 1.5677 |
| 0.5598 | 38.88 | 243 | 1.5853 |
| 0.4793 | 40.0 | 250 | 1.5951 |
| 0.5587 | 40.96 | 256 | 1.5850 |
| 0.5577 | 41.92 | 262 | 1.5904 |
| 0.5568 | 42.88 | 268 | 1.5913 |
| 0.477 | 44.0 | 275 | 1.5959 |
| 0.5553 | 44.96 | 281 | 1.6042 |
| 0.5556 | 45.92 | 287 | 1.6082 |
| 0.5549 | 46.88 | 293 | 1.6075 |
| 0.4749 | 48.0 | 300 | 1.6079 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.39.3
- Pytorch 2.1.2
- Datasets 2.18.0
- Tokenizers 0.15.2