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---
license: apache-2.0
library_name: peft
tags:
- generated_from_trainer
base_model: mistralai/Mistral-7B-v0.1
model-index:
- name: org_aug_a
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. -->
# org_aug_a
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: 0.8808
- F1 Micro: 0.6615
- F1 Macro: 0.6476
- F1 Weighted: 0.6615
## 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: 32
- eval_batch_size: 32
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- training_steps: 400
### Training results
| Training Loss | Epoch | Step | Validation Loss | F1 Micro | F1 Macro | F1 Weighted |
|:-------------:|:------:|:----:|:---------------:|:--------:|:--------:|:-----------:|
| 2.2195 | 0.0154 | 25 | 1.5207 | 0.5691 | 0.5521 | 0.5694 |
| 1.4371 | 0.0308 | 50 | 1.2747 | 0.6089 | 0.5857 | 0.6052 |
| 1.2556 | 0.0462 | 75 | 1.1545 | 0.6304 | 0.6036 | 0.6240 |
| 1.2415 | 0.0615 | 100 | 1.0691 | 0.6320 | 0.6132 | 0.6301 |
| 0.9864 | 0.0769 | 125 | 1.0264 | 0.6399 | 0.6278 | 0.6411 |
| 1.0647 | 0.0923 | 150 | 0.9918 | 0.6510 | 0.6266 | 0.6455 |
| 0.9849 | 0.1077 | 175 | 0.9679 | 0.6576 | 0.6317 | 0.6511 |
| 1.0067 | 0.1231 | 200 | 0.9383 | 0.6501 | 0.6384 | 0.6513 |
| 0.8928 | 0.1385 | 225 | 0.9243 | 0.6620 | 0.6405 | 0.6579 |
| 0.9858 | 0.1538 | 250 | 0.9132 | 0.6627 | 0.6405 | 0.6582 |
| 0.9085 | 0.1692 | 275 | 0.9011 | 0.6575 | 0.6446 | 0.6581 |
| 1.0059 | 0.1846 | 300 | 0.9018 | 0.6686 | 0.6436 | 0.6623 |
| 0.8939 | 0.2 | 325 | 0.8928 | 0.6682 | 0.6448 | 0.6629 |
| 0.864 | 0.2154 | 350 | 0.8833 | 0.6622 | 0.6478 | 0.6619 |
| 0.9499 | 0.2308 | 375 | 0.8837 | 0.6585 | 0.6463 | 0.6593 |
| 0.9721 | 0.2462 | 400 | 0.8808 | 0.6615 | 0.6476 | 0.6615 |
### Framework versions
- PEFT 0.10.0
- Transformers 4.40.2
- Pytorch 2.3.0+cu118
- Datasets 2.19.0
- Tokenizers 0.19.1 |