|
--- |
|
license: apache-2.0 |
|
base_model: alex-miller/ODABert |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- accuracy |
|
- f1 |
|
- precision |
|
- recall |
|
model-index: |
|
- name: iati-climate-multi-classifier-weighted2 |
|
results: [] |
|
--- |
|
|
|
<!-- This model card has been generated automatically according to the information the Trainer had access to. You |
|
should probably proofread and complete it, then remove this comment. --> |
|
|
|
# iati-climate-multi-classifier-weighted2 |
|
|
|
This model is a fine-tuned version of [alex-miller/ODABert](https://huggingface.co/alex-miller/ODABert) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 0.7080 |
|
- Accuracy: 0.8541 |
|
- F1: 0.7121 |
|
- Precision: 0.6265 |
|
- Recall: 0.8248 |
|
|
|
## 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-06 |
|
- train_batch_size: 24 |
|
- eval_batch_size: 24 |
|
- seed: 42 |
|
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 |
|
- lr_scheduler_type: linear |
|
- num_epochs: 20 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Accuracy | F1 | Validation Loss | Precision | Recall | |
|
|:-------------:|:-----:|:-----:|:--------:|:------:|:---------------:|:---------:|:------:| |
|
| 0.7689 | 1.0 | 1951 | 0.7993 | 0.6421 | 0.6477 | 0.5264 | 0.8230 | |
|
| 0.6217 | 2.0 | 3902 | 0.8303 | 0.6737 | 0.6269 | 0.5814 | 0.8010 | |
|
| 0.5834 | 3.0 | 5853 | 0.8266 | 0.6761 | 0.6101 | 0.5715 | 0.8276 | |
|
| 0.5571 | 4.0 | 7804 | 0.8461 | 0.6933 | 0.6169 | 0.6144 | 0.7954 | |
|
| 0.5323 | 5.0 | 9755 | 0.8366 | 0.6869 | 0.6050 | 0.5913 | 0.8194 | |
|
| 0.5126 | 6.0 | 11706 | 0.8327 | 0.6867 | 0.6047 | 0.5815 | 0.8385 | |
|
| 0.4968 | 7.0 | 13657 | 0.8408 | 0.6938 | 0.6098 | 0.5989 | 0.8244 | |
|
| 0.4893 | 8.0 | 15608 | 0.6040 | 0.8348 | 0.6895 | 0.5854 | 0.8387 | |
|
| 0.4702 | 9.0 | 17559 | 0.6342 | 0.8508 | 0.7050 | 0.6211 | 0.8151 | |
|
| 0.4514 | 10.0 | 19510 | 0.6210 | 0.8383 | 0.6946 | 0.5918 | 0.8404 | |
|
| 0.4323 | 11.0 | 21461 | 0.6340 | 0.8402 | 0.6991 | 0.5943 | 0.8487 | |
|
| 0.4193 | 12.0 | 23412 | 0.6407 | 0.8433 | 0.7005 | 0.6020 | 0.8375 | |
|
| 0.407 | 13.0 | 25363 | 0.6602 | 0.8526 | 0.7094 | 0.6237 | 0.8223 | |
|
| 0.3944 | 14.0 | 27314 | 0.6588 | 0.8441 | 0.7026 | 0.6029 | 0.8419 | |
|
| 0.3834 | 15.0 | 29265 | 0.6881 | 0.8529 | 0.7110 | 0.6233 | 0.8274 | |
|
| 0.3738 | 16.0 | 31216 | 0.7029 | 0.8575 | 0.7146 | 0.6359 | 0.8155 | |
|
| 0.3686 | 17.0 | 33167 | 0.6929 | 0.8524 | 0.7102 | 0.6224 | 0.8271 | |
|
| 0.3607 | 18.0 | 35118 | 0.7069 | 0.8545 | 0.7127 | 0.6272 | 0.8253 | |
|
| 0.3556 | 19.0 | 37069 | 0.7072 | 0.8543 | 0.7118 | 0.6274 | 0.8225 | |
|
| 0.3523 | 20.0 | 39020 | 0.7080 | 0.8541 | 0.7121 | 0.6265 | 0.8248 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.41.0 |
|
- Pytorch 2.0.1 |
|
- Datasets 2.19.1 |
|
- Tokenizers 0.19.1 |
|
|
