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---
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
|