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---
license: mit
tags:
- generated_from_trainer
metrics:
- matthews_correlation
model-index:
- name: TestMeanFraction2
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. -->
# TestMeanFraction2
This model is a fine-tuned version of [cmarkea/distilcamembert-base](https://huggingface.co/cmarkea/distilcamembert-base) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.3967
- Matthews Correlation: 0.2537
## Model description
More information needed
## Intended uses & limitations
"La panique totale" Cette femme trouve une énorme araignée suspendue à sa douche.
## 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
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 8
### Training results
| Training Loss | Epoch | Step | Validation Loss | Matthews Correlation |
|:-------------:|:-----:|:----:|:---------------:|:--------------------:|
| No log | 0.13 | 50 | 1.1126 | 0.1589 |
| No log | 0.25 | 100 | 1.0540 | 0.1884 |
| No log | 0.38 | 150 | 1.1533 | 0.0818 |
| No log | 0.51 | 200 | 1.0676 | 0.1586 |
| No log | 0.64 | 250 | 0.9949 | 0.2280 |
| No log | 0.76 | 300 | 1.0343 | 0.2629 |
| No log | 0.89 | 350 | 1.0203 | 0.2478 |
| No log | 1.02 | 400 | 1.0041 | 0.2752 |
| No log | 1.15 | 450 | 1.0808 | 0.2256 |
| 1.023 | 1.27 | 500 | 1.0029 | 0.2532 |
| 1.023 | 1.4 | 550 | 1.0204 | 0.2508 |
| 1.023 | 1.53 | 600 | 1.1377 | 0.1689 |
| 1.023 | 1.65 | 650 | 1.0499 | 0.2926 |
| 1.023 | 1.78 | 700 | 1.0441 | 0.2474 |
| 1.023 | 1.91 | 750 | 1.0279 | 0.2611 |
| 1.023 | 2.04 | 800 | 1.1511 | 0.2804 |
| 1.023 | 2.16 | 850 | 1.2381 | 0.2512 |
| 1.023 | 2.29 | 900 | 1.3340 | 0.2385 |
| 1.023 | 2.42 | 950 | 1.4372 | 0.2842 |
| 0.7325 | 2.54 | 1000 | 1.3967 | 0.2537 |
| 0.7325 | 2.67 | 1050 | 1.4272 | 0.2624 |
| 0.7325 | 2.8 | 1100 | 1.3869 | 0.1941 |
| 0.7325 | 2.93 | 1150 | 1.4983 | 0.2063 |
| 0.7325 | 3.05 | 1200 | 1.4959 | 0.2409 |
### Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0a0+0aef44c
- Datasets 2.0.0
- Tokenizers 0.11.6
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