metadata
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: >-
DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_False
results: []
DistilBERTFINAL_ctxSentence_TRAIN_webDiscourse_TEST_NULL_second_train_set_null_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: 3.2555
- Precision: 1.0
- Recall: 0.0200
- F1: 0.0393
- Accuracy: 0.0486
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 | 95 | 0.5756 | nan | 0.0 | nan | 0.715 |
| No log | 2.0 | 190 | 0.5340 | 0.6429 | 0.1579 | 0.2535 | 0.735 |
| No log | 3.0 | 285 | 0.5298 | 0.5833 | 0.3684 | 0.4516 | 0.745 |
| No log | 4.0 | 380 | 0.5325 | 0.5789 | 0.3860 | 0.4632 | 0.745 |
| No log | 5.0 | 475 | 0.5452 | 0.4815 | 0.4561 | 0.4685 | 0.705 |
Framework versions
- Transformers 4.15.0
- Pytorch 1.10.1+cu113
- Datasets 1.18.0
- Tokenizers 0.10.3