| --- |
| 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 | |
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|
|
| ### Framework versions |
|
|
| - Transformers 4.18.0 |
| - Pytorch 1.10.0a0+0aef44c |
| - Datasets 2.0.0 |
| - Tokenizers 0.11.6 |
|
|
