---
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: 1.1404
- F1: 0.6842

## 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: 3.887e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 44
- num_epochs: 20

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     |
|:-------------:|:-----:|:----:|:---------------:|:------:|
| 0.9899        | 1.0   | 199  | 0.8943          | 0.5434 |
| 0.5878        | 2.0   | 398  | 0.8040          | 0.6147 |
| 0.3657        | 3.0   | 597  | 0.8181          | 0.6132 |
| 0.2319        | 4.0   | 796  | 0.7678          | 0.6420 |
| 0.1497        | 5.0   | 995  | 0.8567          | 0.6385 |
| 0.103         | 6.0   | 1194 | 0.8607          | 0.6603 |
| 0.066         | 7.0   | 1393 | 0.8711          | 0.6414 |
| 0.0464        | 8.0   | 1592 | 0.9418          | 0.6908 |
| 0.0353        | 9.0   | 1791 | 0.9508          | 0.6815 |
| 0.0274        | 10.0  | 1990 | 0.9942          | 0.6771 |
| 0.0232        | 11.0  | 2189 | 1.0016          | 0.6846 |
| 0.0201        | 12.0  | 2388 | 1.0156          | 0.6914 |
| 0.018         | 13.0  | 2587 | 1.0488          | 0.6958 |
| 0.0164        | 14.0  | 2786 | 1.0911          | 0.6808 |
| 0.0153        | 15.0  | 2985 | 1.0688          | 0.6901 |
| 0.0143        | 16.0  | 3184 | 1.1095          | 0.6798 |
| 0.0135        | 17.0  | 3383 | 1.1022          | 0.6794 |
| 0.0129        | 18.0  | 3582 | 1.1310          | 0.6812 |
| 0.0124        | 19.0  | 3781 | 1.1359          | 0.6842 |
| 0.0123        | 20.0  | 3980 | 1.1404          | 0.6842 |


### Framework versions

- Transformers 4.38.2
- Pytorch 2.1.0+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2