metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: _ctxSentence_TRAIN_all_TEST_french_second_train_set_french_False
results: []
_ctxSentence_TRAIN_all_TEST_french_second_train_set_french_False
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: 0.4936
- Precision: 0.8189
- Recall: 0.9811
- F1: 0.8927
- Accuracy: 0.8120
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 | 13 | 0.5150 | 0.7447 | 1.0 | 0.8537 | 0.7447 |
| No log | 2.0 | 26 | 0.5565 | 0.7447 | 1.0 | 0.8537 | 0.7447 |
| No log | 3.0 | 39 | 0.5438 | 0.7778 | 1.0 | 0.8750 | 0.7872 |
| No log | 4.0 | 52 | 0.5495 | 0.7778 | 1.0 | 0.8750 | 0.7872 |
| No log | 5.0 | 65 | 0.5936 | 0.7778 | 1.0 | 0.8750 | 0.7872 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3