metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: >-
DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True
results: []
DistilBERTFINAL_ctxSentence_TRAIN_all_TEST_french_second_train_set_NULL_True
This model is a fine-tuned version of cardiffnlp/twitter-roberta-base on the None dataset. It achieves the following results on the evaluation set:
- Loss: 0.4024
- Precision: 0.8643
- Recall: 0.9769
- F1: 0.9171
- Accuracy: 0.8594
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: 1e-05
- 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
- num_epochs: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| No log | 1.0 | 130 | 0.4920 | 0.7766 | 1.0 | 0.8742 | 0.7766 |
| No log | 2.0 | 260 | 0.4469 | 0.7885 | 1.0 | 0.8818 | 0.7918 |
| No log | 3.0 | 390 | 0.3860 | 0.8248 | 0.9860 | 0.8982 | 0.8265 |
| 0.462 | 4.0 | 520 | 0.3948 | 0.8441 | 0.9832 | 0.9084 | 0.8460 |
| 0.462 | 5.0 | 650 | 0.3694 | 0.8632 | 0.9693 | 0.9132 | 0.8568 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3