metadata
base_model: gechim/metadata-cls-no-gov-8k-v3
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
model-index:
- name: PhobertLexicalMeta-v2
results: []
PhobertLexicalMeta-v2
This model is a fine-tuned version of gechim/metadata-cls-no-gov-8k-v3 on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3926
- Accuracy: 0.9062
- F1: 0.8781
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|---|---|---|---|---|---|
| No log | 0.8772 | 100 | 0.2699 | 0.9080 | 0.8801 |
| 0.1564 | 1.7544 | 200 | 0.2984 | 0.9011 | 0.8723 |
| 0.073 | 2.6316 | 300 | 0.3218 | 0.8987 | 0.8705 |
| 0.0502 | 3.5088 | 400 | 0.3472 | 0.8927 | 0.8641 |
| 0.0326 | 4.3860 | 500 | 0.3627 | 0.8941 | 0.8635 |
| 0.0285 | 5.2632 | 600 | 0.3752 | 0.8964 | 0.8685 |
| 0.0179 | 6.1404 | 700 | 0.3666 | 0.9025 | 0.8734 |
| 0.0156 | 7.0175 | 800 | 0.3759 | 0.9043 | 0.8748 |
| 0.0156 | 7.8947 | 900 | 0.3830 | 0.9080 | 0.8788 |
| 0.011 | 8.7719 | 1000 | 0.3917 | 0.9039 | 0.8746 |
| 0.0092 | 9.6491 | 1100 | 0.3926 | 0.9062 | 0.8781 |
Framework versions
- Transformers 4.43.3
- Pytorch 2.1.2
- Datasets 2.20.0
- Tokenizers 0.19.1