metadata
license: apache-2.0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
- precision
- recall
model-index:
- name: bert-bert-cased-first512-Conflict
results: []
bert-bert-cased-first512-Conflict
conv_text = '\n'.join([utt.text for utt in conv.get_chronological_utterance_list()])
This model is a fine-tuned version of bert-base-cased on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.6932
- F1: 0.6667
- Accuracy: 0.5
- Precision: 0.5
- Recall: 1.0
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: 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: 5
Training results
| Training Loss | Epoch | Step | Validation Loss | F1 | Accuracy | Precision | Recall |
|---|---|---|---|---|---|---|---|
| 0.7098 | 1.0 | 685 | 0.6945 | 0.0 | 0.5 | 0.0 | 0.0 |
| 0.7046 | 2.0 | 1370 | 0.6997 | 0.6667 | 0.5 | 0.5 | 1.0 |
| 0.7013 | 3.0 | 2055 | 0.6949 | 0.6667 | 0.5 | 0.5 | 1.0 |
| 0.7027 | 4.0 | 2740 | 0.6931 | 0.6667 | 0.5 | 0.5 | 1.0 |
| 0.702 | 5.0 | 3425 | 0.6932 | 0.6667 | 0.5 | 0.5 | 1.0 |
Framework versions
- Transformers 4.18.0
- Pytorch 1.10.0+cu111
- Datasets 2.1.0
- Tokenizers 0.12.1