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---
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tags:
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- generated_from_trainer
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metrics:
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- precision
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- recall
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- f1
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- accuracy
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model-index:
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- name: DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_french_False
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results: []
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---
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<!-- This model card has been generated automatically according to the information the Trainer had access to. You
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should probably proofread and complete it, then remove this comment. -->
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# DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_french_False
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This model is a fine-tuned version of [cardiffnlp/twitter-roberta-base](https://huggingface.co/cardiffnlp/twitter-roberta-base) on the None dataset.
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It achieves the following results on the evaluation set:
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- Loss: 0.3931
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- Precision: 0.8809
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- Recall: 0.9501
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- F1: 0.9142
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- Accuracy: 0.8579
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## Model description
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More information needed
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## Intended uses & limitations
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More information needed
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## Training and evaluation data
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More information needed
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## Training procedure
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### Training hyperparameters
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The following hyperparameters were used during training:
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- learning_rate: 1e-05
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- train_batch_size: 32
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- eval_batch_size: 32
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- seed: 42
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- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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- lr_scheduler_type: linear
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- num_epochs: 5
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### Training results
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| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
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|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
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| No log | 1.0 | 130 | 0.4105 | 0.8568 | 0.9645 | 0.9075 | 0.8438 |
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| No log | 2.0 | 260 | 0.4006 | 0.8520 | 0.9754 | 0.9096 | 0.8460 |
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| No log | 3.0 | 390 | 0.4112 | 0.8543 | 0.9454 | 0.8975 | 0.8286 |
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| 0.376 | 4.0 | 520 | 0.4278 | 0.8711 | 0.9235 | 0.8966 | 0.8308 |
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| 0.376 | 5.0 | 650 | 0.4430 | 0.8655 | 0.9317 | 0.8974 | 0.8308 |
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### Framework versions
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- Transformers 4.15.0
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- Pytorch 1.10.1+cu113
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- Datasets 1.18.0
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- Tokenizers 0.10.3
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