File size: 2,721 Bytes
8f37a3f |
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 75 76 77 78 79 80 81 82 83 |
---
license: apache-2.0
base_model: facebook/dinov2-base
tags:
- generated_from_trainer
metrics:
- precision
- recall
- f1
model-index:
- name: outputs
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. -->
# outputs
This model is a fine-tuned version of [facebook/dinov2-base](https://huggingface.co/facebook/dinov2-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.0742
- Precision: 0.9306
- Recall: 0.8969
- F1: 0.9135
## 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-06
- train_batch_size: 16
- eval_batch_size: 16
- seed: 42
- gradient_accumulation_steps: 8
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- num_epochs: 15
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 |
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|
| 0.5948 | 0.98 | 39 | 0.4487 | 0.1103 | 0.0658 | 0.0824 |
| 0.2211 | 1.98 | 79 | 0.2079 | 0.8179 | 0.5614 | 0.6658 |
| 0.1241 | 2.98 | 119 | 0.1378 | 0.8880 | 0.7390 | 0.8067 |
| 0.0954 | 3.99 | 159 | 0.1117 | 0.8916 | 0.8114 | 0.8496 |
| 0.0801 | 4.99 | 199 | 0.0980 | 0.9167 | 0.8322 | 0.8724 |
| 0.0716 | 5.99 | 239 | 0.0875 | 0.9245 | 0.8596 | 0.8909 |
| 0.0641 | 7.0 | 279 | 0.0871 | 0.9231 | 0.8421 | 0.8807 |
| 0.0615 | 8.0 | 319 | 0.0804 | 0.9318 | 0.8838 | 0.9071 |
| 0.056 | 8.98 | 358 | 0.0793 | 0.9257 | 0.8882 | 0.9065 |
| 0.0541 | 9.98 | 398 | 0.0761 | 0.9335 | 0.8925 | 0.9126 |
| 0.0532 | 10.98 | 438 | 0.0767 | 0.9339 | 0.8827 | 0.9076 |
| 0.053 | 11.99 | 478 | 0.0758 | 0.9312 | 0.8904 | 0.9103 |
| 0.048 | 12.99 | 518 | 0.0743 | 0.9324 | 0.8925 | 0.9120 |
| 0.047 | 13.99 | 558 | 0.0750 | 0.9303 | 0.8925 | 0.9110 |
| 0.0476 | 14.67 | 585 | 0.0742 | 0.9306 | 0.8969 | 0.9135 |
### Framework versions
- Transformers 4.37.0
- Pytorch 1.13.1+cu117
- Datasets 2.18.0
- Tokenizers 0.15.2
|