---
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: 0.2194
- F1: 0.6392
- Roc Auc: 0.7794
- Accuracy: 0.1228

## 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     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| No log        | 1.0   | 50   | 0.3035          | 0.1236 | 0.5447  | 0.0      |
| No log        | 2.0   | 100  | 0.2696          | 0.3655 | 0.6420  | 0.0877   |
| No log        | 3.0   | 150  | 0.2468          | 0.3611 | 0.6390  | 0.0877   |
| No log        | 4.0   | 200  | 0.2387          | 0.4837 | 0.6999  | 0.0877   |
| No log        | 5.0   | 250  | 0.2311          | 0.5244 | 0.7164  | 0.0526   |
| No log        | 6.0   | 300  | 0.2215          | 0.5768 | 0.7326  | 0.1053   |
| No log        | 7.0   | 350  | 0.2242          | 0.6033 | 0.7593  | 0.0877   |
| No log        | 8.0   | 400  | 0.2155          | 0.6350 | 0.7624  | 0.0877   |
| No log        | 9.0   | 450  | 0.2227          | 0.6294 | 0.7746  | 0.1228   |
| 0.1644        | 10.0  | 500  | 0.2156          | 0.6412 | 0.7772  | 0.1053   |
| 0.1644        | 11.0  | 550  | 0.2176          | 0.6332 | 0.7715  | 0.1053   |
| 0.1644        | 12.0  | 600  | 0.2182          | 0.6430 | 0.7816  | 0.1228   |
| 0.1644        | 13.0  | 650  | 0.2190          | 0.6390 | 0.7794  | 0.1228   |
| 0.1644        | 14.0  | 700  | 0.2184          | 0.6377 | 0.7788  | 0.1228   |
| 0.1644        | 15.0  | 750  | 0.2194          | 0.6392 | 0.7794  | 0.1228   |


### Framework versions

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