---
license: mit
base_model: avsolatorio/GIST-large-Embedding-v0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: my-clf-microsoft
  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-microsoft

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: 0.2381
- F1: 0.5822
- Roc Auc: 0.7634
- Accuracy: 0.1786

## 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: 16

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 50   | 0.3147          | 0.0656 | 0.5250  | 0.0      |
| No log        | 2.0   | 100  | 0.2808          | 0.2809 | 0.6082  | 0.0536   |
| No log        | 3.0   | 150  | 0.2539          | 0.3854 | 0.6521  | 0.0357   |
| No log        | 4.0   | 200  | 0.2451          | 0.4085 | 0.6582  | 0.0714   |
| No log        | 5.0   | 250  | 0.2351          | 0.4365 | 0.6734  | 0.1071   |
| No log        | 6.0   | 300  | 0.2361          | 0.4977 | 0.7133  | 0.125    |
| No log        | 7.0   | 350  | 0.2325          | 0.5629 | 0.7433  | 0.1607   |
| No log        | 8.0   | 400  | 0.2294          | 0.5488 | 0.7401  | 0.1964   |
| No log        | 9.0   | 450  | 0.2336          | 0.5750 | 0.7567  | 0.1964   |
| 0.1718        | 10.0  | 500  | 0.2342          | 0.5695 | 0.7563  | 0.1964   |
| 0.1718        | 11.0  | 550  | 0.2354          | 0.5809 | 0.7648  | 0.1964   |
| 0.1718        | 12.0  | 600  | 0.2349          | 0.5862 | 0.7658  | 0.1786   |
| 0.1718        | 13.0  | 650  | 0.2390          | 0.5811 | 0.7645  | 0.1786   |
| 0.1718        | 14.0  | 700  | 0.2367          | 0.5841 | 0.7633  | 0.2143   |
| 0.1718        | 15.0  | 750  | 0.2376          | 0.5778 | 0.7606  | 0.1786   |
| 0.1718        | 16.0  | 800  | 0.2381          | 0.5822 | 0.7634  | 0.1786   |


### Framework versions

- Transformers 4.38.1
- Pytorch 2.1.2
- Datasets 2.1.0
- Tokenizers 0.15.2