---
license: mit
base_model: avsolatorio/GIST-large-Embedding-v0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
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: 0.2391
- F1: 0.5650
- Roc Auc: 0.7487
- 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   | 0.3095          | 0.1123 | 0.5442  | 0.0351   |
| No log        | 2.0   | 100  | 0.2862          | 0.2744 | 0.6015  | 0.0702   |
| No log        | 3.0   | 150  | 0.2642          | 0.3740 | 0.6488  | 0.0877   |
| No log        | 4.0   | 200  | 0.2563          | 0.4429 | 0.6792  | 0.0526   |
| No log        | 5.0   | 250  | 0.2492          | 0.5030 | 0.7178  | 0.0877   |
| No log        | 6.0   | 300  | 0.2323          | 0.5296 | 0.7199  | 0.1228   |
| No log        | 7.0   | 350  | 0.2372          | 0.5433 | 0.7326  | 0.1053   |
| No log        | 8.0   | 400  | 0.2326          | 0.5371 | 0.7279  | 0.1053   |
| No log        | 9.0   | 450  | 0.2346          | 0.5587 | 0.7382  | 0.1404   |
| 0.1673        | 10.0  | 500  | 0.2393          | 0.5819 | 0.7534  | 0.1053   |
| 0.1673        | 11.0  | 550  | 0.2370          | 0.5656 | 0.7471  | 0.1053   |
| 0.1673        | 12.0  | 600  | 0.2374          | 0.5680 | 0.7479  | 0.1404   |
| 0.1673        | 13.0  | 650  | 0.2392          | 0.5680 | 0.7500  | 0.1228   |
| 0.1673        | 14.0  | 700  | 0.2398          | 0.5650 | 0.7487  | 0.1228   |
| 0.1673        | 15.0  | 750  | 0.2391          | 0.5650 | 0.7487  | 0.1228   |


### Framework versions

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