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---
license: mit
base_model: camembert-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: camembert_classification_tools_qlora
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. -->
# camembert_classification_tools_qlora
This model is a fine-tuned version of [camembert-base](https://huggingface.co/camembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 0.7844
- Accuracy: 0.7
## 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: 24
- eval_batch_size: 192
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 60
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| No log | 1.0 | 5 | 2.0913 | 0.05 |
| No log | 2.0 | 10 | 2.1000 | 0.05 |
| No log | 3.0 | 15 | 2.0985 | 0.1 |
| No log | 4.0 | 20 | 2.0854 | 0.15 |
| No log | 5.0 | 25 | 2.0667 | 0.275 |
| No log | 6.0 | 30 | 2.0459 | 0.35 |
| No log | 7.0 | 35 | 2.0092 | 0.325 |
| No log | 8.0 | 40 | 1.9610 | 0.375 |
| No log | 9.0 | 45 | 1.9182 | 0.4 |
| No log | 10.0 | 50 | 1.8769 | 0.425 |
| No log | 11.0 | 55 | 1.8349 | 0.425 |
| No log | 12.0 | 60 | 1.7894 | 0.425 |
| No log | 13.0 | 65 | 1.7395 | 0.425 |
| No log | 14.0 | 70 | 1.6914 | 0.425 |
| No log | 15.0 | 75 | 1.6472 | 0.45 |
| No log | 16.0 | 80 | 1.6029 | 0.45 |
| No log | 17.0 | 85 | 1.5619 | 0.475 |
| No log | 18.0 | 90 | 1.5190 | 0.5 |
| No log | 19.0 | 95 | 1.4621 | 0.575 |
| No log | 20.0 | 100 | 1.4180 | 0.55 |
| No log | 21.0 | 105 | 1.3786 | 0.575 |
| No log | 22.0 | 110 | 1.3384 | 0.575 |
| No log | 23.0 | 115 | 1.2975 | 0.625 |
| No log | 24.0 | 120 | 1.2561 | 0.65 |
| No log | 25.0 | 125 | 1.2164 | 0.675 |
| No log | 26.0 | 130 | 1.1839 | 0.675 |
| No log | 27.0 | 135 | 1.1602 | 0.65 |
| No log | 28.0 | 140 | 1.1304 | 0.625 |
| No log | 29.0 | 145 | 1.1029 | 0.625 |
| No log | 30.0 | 150 | 1.0744 | 0.625 |
| No log | 31.0 | 155 | 1.0482 | 0.625 |
| No log | 32.0 | 160 | 1.0197 | 0.675 |
| No log | 33.0 | 165 | 0.9967 | 0.725 |
| No log | 34.0 | 170 | 0.9793 | 0.725 |
| No log | 35.0 | 175 | 0.9640 | 0.725 |
| No log | 36.0 | 180 | 0.9502 | 0.675 |
| No log | 37.0 | 185 | 0.9390 | 0.65 |
| No log | 38.0 | 190 | 0.9183 | 0.7 |
| No log | 39.0 | 195 | 0.8987 | 0.725 |
| No log | 40.0 | 200 | 0.8817 | 0.775 |
| No log | 41.0 | 205 | 0.8684 | 0.725 |
| No log | 42.0 | 210 | 0.8611 | 0.7 |
| No log | 43.0 | 215 | 0.8607 | 0.7 |
| No log | 44.0 | 220 | 0.8592 | 0.7 |
| No log | 45.0 | 225 | 0.8471 | 0.725 |
| No log | 46.0 | 230 | 0.8306 | 0.725 |
| No log | 47.0 | 235 | 0.8189 | 0.75 |
| No log | 48.0 | 240 | 0.8136 | 0.725 |
| No log | 49.0 | 245 | 0.8142 | 0.7 |
| No log | 50.0 | 250 | 0.8092 | 0.7 |
| No log | 51.0 | 255 | 0.8053 | 0.75 |
| No log | 52.0 | 260 | 0.7995 | 0.75 |
| No log | 53.0 | 265 | 0.7917 | 0.75 |
| No log | 54.0 | 270 | 0.7901 | 0.725 |
| No log | 55.0 | 275 | 0.7910 | 0.7 |
| No log | 56.0 | 280 | 0.7904 | 0.7 |
| No log | 57.0 | 285 | 0.7884 | 0.7 |
| No log | 58.0 | 290 | 0.7863 | 0.7 |
| No log | 59.0 | 295 | 0.7851 | 0.7 |
| No log | 60.0 | 300 | 0.7844 | 0.7 |
### Framework versions
- Transformers 4.34.0
- Pytorch 2.0.1+cu117
- Datasets 2.14.5
- Tokenizers 0.14.1
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