---
license: mit
base_model: avsolatorio/GIST-large-Embedding-v0
tags:
- generated_from_trainer
metrics:
- f1
- accuracy
model-index:
- name: output
  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. -->

# output

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: 0.3318
- F1: 0.6260
- Roc Auc: 0.7856
- 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 40
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | F1     | Roc Auc | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:------:|:-------:|:--------:|
| 0.4488        | 1.0   | 25   | 0.3675          | 0.0779 | 0.5325  | 0.0179   |
| 0.3356        | 2.0   | 50   | 0.3240          | 0.1910 | 0.5740  | 0.0536   |
| 0.2818        | 3.0   | 75   | 0.2998          | 0.3079 | 0.6141  | 0.0357   |
| 0.2346        | 4.0   | 100  | 0.2767          | 0.4724 | 0.6938  | 0.0893   |
| 0.1954        | 5.0   | 125  | 0.2833          | 0.4403 | 0.6850  | 0.0714   |
| 0.1605        | 6.0   | 150  | 0.2706          | 0.5153 | 0.7220  | 0.0536   |
| 0.134         | 7.0   | 175  | 0.2719          | 0.5218 | 0.7311  | 0.1071   |
| 0.1133        | 8.0   | 200  | 0.2776          | 0.5369 | 0.7475  | 0.0714   |
| 0.0935        | 9.0   | 225  | 0.2626          | 0.5796 | 0.7555  | 0.1429   |
| 0.0808        | 10.0  | 250  | 0.2669          | 0.5778 | 0.7576  | 0.125    |
| 0.0694        | 11.0  | 275  | 0.2633          | 0.5963 | 0.7731  | 0.1429   |
| 0.0573        | 12.0  | 300  | 0.2661          | 0.5658 | 0.7612  | 0.1071   |
| 0.0496        | 13.0  | 325  | 0.2543          | 0.6004 | 0.7643  | 0.1429   |
| 0.0429        | 14.0  | 350  | 0.2735          | 0.5936 | 0.7729  | 0.1071   |
| 0.0366        | 15.0  | 375  | 0.2694          | 0.6179 | 0.7848  | 0.1429   |
| 0.0323        | 16.0  | 400  | 0.2724          | 0.6217 | 0.7865  | 0.1429   |
| 0.0289        | 17.0  | 425  | 0.2821          | 0.6157 | 0.7734  | 0.1786   |
| 0.0257        | 18.0  | 450  | 0.2787          | 0.6399 | 0.7854  | 0.1786   |
| 0.0229        | 19.0  | 475  | 0.2887          | 0.6114 | 0.7774  | 0.1071   |
| 0.02          | 20.0  | 500  | 0.2807          | 0.6394 | 0.7970  | 0.1429   |
| 0.0182        | 21.0  | 525  | 0.2852          | 0.6343 | 0.7797  | 0.1786   |
| 0.0165        | 22.0  | 550  | 0.2899          | 0.6132 | 0.7774  | 0.1607   |
| 0.0148        | 23.0  | 575  | 0.3000          | 0.6285 | 0.7888  | 0.1607   |
| 0.0136        | 24.0  | 600  | 0.2950          | 0.6409 | 0.7908  | 0.1429   |
| 0.0123        | 25.0  | 625  | 0.3034          | 0.6165 | 0.7815  | 0.1607   |
| 0.0112        | 26.0  | 650  | 0.3061          | 0.6384 | 0.7949  | 0.1607   |
| 0.0103        | 27.0  | 675  | 0.3041          | 0.6371 | 0.7906  | 0.1964   |
| 0.0095        | 28.0  | 700  | 0.3189          | 0.6204 | 0.7836  | 0.1429   |
| 0.009         | 29.0  | 725  | 0.3115          | 0.6267 | 0.7890  | 0.1786   |
| 0.0083        | 30.0  | 750  | 0.3168          | 0.6264 | 0.7856  | 0.1786   |
| 0.008         | 31.0  | 775  | 0.3199          | 0.6320 | 0.7866  | 0.1786   |
| 0.0075        | 32.0  | 800  | 0.3271          | 0.6208 | 0.7839  | 0.1607   |
| 0.0072        | 33.0  | 825  | 0.3219          | 0.6240 | 0.7856  | 0.1607   |
| 0.0068        | 34.0  | 850  | 0.3257          | 0.6312 | 0.7849  | 0.1786   |
| 0.0065        | 35.0  | 875  | 0.3249          | 0.6247 | 0.7855  | 0.1786   |
| 0.0063        | 36.0  | 900  | 0.3296          | 0.6291 | 0.7881  | 0.1786   |
| 0.0062        | 37.0  | 925  | 0.3302          | 0.6227 | 0.7844  | 0.1786   |
| 0.006         | 38.0  | 950  | 0.3287          | 0.6260 | 0.7856  | 0.1786   |
| 0.0058        | 39.0  | 975  | 0.3317          | 0.6260 | 0.7856  | 0.1786   |
| 0.0058        | 40.0  | 1000 | 0.3318          | 0.6260 | 0.7856  | 0.1786   |


### Framework versions

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