|
--- |
|
license: mit |
|
base_model: avsolatorio/GIST-large-Embedding-v0 |
|
tags: |
|
- generated_from_trainer |
|
metrics: |
|
- f1 |
|
model-index: |
|
- name: my-clf |
|
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. --> |
|
|
|
# my-clf |
|
|
|
This model is a fine-tuned version of [avsolatorio/GIST-large-Embedding-v0](https://huggingface.co./avsolatorio/GIST-large-Embedding-v0) on the None dataset. |
|
It achieves the following results on the evaluation set: |
|
- Loss: 1.1824 |
|
- F1: 0.6653 |
|
|
|
## 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: 15 |
|
|
|
### Training results |
|
|
|
| Training Loss | Epoch | Step | Validation Loss | F1 | |
|
|:-------------:|:-----:|:----:|:---------------:|:------:| |
|
| 0.1488 | 1.0 | 100 | 1.1930 | 0.6355 | |
|
| 0.1232 | 2.0 | 200 | 0.9133 | 0.6473 | |
|
| 0.0797 | 3.0 | 300 | 1.0238 | 0.6603 | |
|
| 0.0522 | 4.0 | 400 | 0.9822 | 0.6713 | |
|
| 0.0366 | 5.0 | 500 | 1.0208 | 0.6664 | |
|
| 0.0252 | 6.0 | 600 | 0.9856 | 0.6755 | |
|
| 0.0199 | 7.0 | 700 | 1.0628 | 0.6665 | |
|
| 0.0174 | 8.0 | 800 | 1.0667 | 0.6651 | |
|
| 0.0155 | 9.0 | 900 | 1.0934 | 0.6664 | |
|
| 0.0141 | 10.0 | 1000 | 1.1478 | 0.6676 | |
|
| 0.0131 | 11.0 | 1100 | 1.1644 | 0.6707 | |
|
| 0.0124 | 12.0 | 1200 | 1.1661 | 0.6638 | |
|
| 0.0122 | 13.0 | 1300 | 1.1781 | 0.6648 | |
|
| 0.0118 | 14.0 | 1400 | 1.1810 | 0.6664 | |
|
| 0.0116 | 15.0 | 1500 | 1.1824 | 0.6653 | |
|
|
|
|
|
### Framework versions |
|
|
|
- Transformers 4.38.2 |
|
- Pytorch 2.1.0+cu118 |
|
- Datasets 2.18.0 |
|
- Tokenizers 0.15.2 |
|
|
