metadata
base_model: YituTech/conv-bert-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
- accuracy
model-index:
- name: conv-bert-base
results: []
conv-bert-base
This model is a fine-tuned version of YituTech/conv-bert-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.2024
- Precision: 0.7686
- Recall: 0.8278
- F1: 0.7971
- Accuracy: 0.9376
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: 2e-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: 3
Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|---|---|---|---|---|---|---|---|
| 0.2235 | 1.0 | 2078 | 0.2225 | 0.7307 | 0.7996 | 0.7636 | 0.9301 |
| 0.1814 | 2.0 | 4156 | 0.1946 | 0.7539 | 0.8257 | 0.7881 | 0.9363 |
| 0.1469 | 3.0 | 6234 | 0.2024 | 0.7686 | 0.8278 | 0.7971 | 0.9376 |
Framework versions
- Transformers 4.35.2
- Pytorch 2.1.0+cu121
- Datasets 2.16.1
- Tokenizers 0.15.1