File size: 2,311 Bytes
ff8c13e |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 |
---
license: apache-2.0
base_model: HooshvareLab/bert-fa-base-uncased-clf-digimag
tags:
- generated_from_trainer
metrics:
- accuracy
- f1
- precision
model-index:
- name: uncased-clf-digimag_v1
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. -->
# uncased-clf-digimag_v1
This model is a fine-tuned version of [HooshvareLab/bert-fa-base-uncased-clf-digimag](https://huggingface.co./HooshvareLab/bert-fa-base-uncased-clf-digimag) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2679
- Accuracy: 0.6413
- F1: 0.6418
- Precision: 0.6458
## 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: 1e-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: 10
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|
| No log | 1.0 | 221 | 1.1415 | 0.4972 | 0.4716 | 0.5696 |
| No log | 2.0 | 442 | 0.9770 | 0.6016 | 0.6029 | 0.6063 |
| 1.0648 | 3.0 | 663 | 0.9529 | 0.6266 | 0.6271 | 0.6304 |
| 1.0648 | 4.0 | 884 | 0.9879 | 0.6470 | 0.6468 | 0.6636 |
| 0.6031 | 5.0 | 1105 | 1.0113 | 0.6311 | 0.6321 | 0.6345 |
| 0.6031 | 6.0 | 1326 | 1.0840 | 0.6356 | 0.6322 | 0.6363 |
| 0.329 | 7.0 | 1547 | 1.1273 | 0.6436 | 0.6438 | 0.6487 |
| 0.329 | 8.0 | 1768 | 1.2089 | 0.6300 | 0.6285 | 0.6291 |
| 0.329 | 9.0 | 1989 | 1.2486 | 0.6345 | 0.6352 | 0.6399 |
| 0.1809 | 10.0 | 2210 | 1.2679 | 0.6413 | 0.6418 | 0.6458 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
|