File size: 3,935 Bytes
329fae3 |
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 84 85 86 87 88 89 90 91 92 |
---
license: apache-2.0
base_model: asapp/sew-d-tiny-100k-ft-ls100h
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
- f1
model-index:
- name: sewd-classifier-aug-large
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. -->
# sewd-classifier-aug-large
This model is a fine-tuned version of [asapp/sew-d-tiny-100k-ft-ls100h](https://huggingface.co/asapp/sew-d-tiny-100k-ft-ls100h) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 3.2094
- Accuracy: 0.1712
- Precision: 0.0867
- Recall: 0.1712
- F1: 0.0887
- Binary: 0.4166
## 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: 32
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 128
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 | Binary |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|:------:|
| No log | 0.1 | 50 | 4.4166 | 0.0108 | 0.0010 | 0.0108 | 0.0013 | 0.1291 |
| No log | 0.2 | 100 | 4.3510 | 0.0135 | 0.0069 | 0.0135 | 0.0026 | 0.1367 |
| No log | 0.29 | 150 | 4.2531 | 0.0323 | 0.0016 | 0.0323 | 0.0030 | 0.2372 |
| No log | 0.39 | 200 | 4.1748 | 0.0350 | 0.0022 | 0.0350 | 0.0039 | 0.2779 |
| No log | 0.49 | 250 | 4.0970 | 0.0431 | 0.0076 | 0.0431 | 0.0094 | 0.2969 |
| No log | 0.59 | 300 | 4.0268 | 0.0499 | 0.0179 | 0.0499 | 0.0116 | 0.3198 |
| No log | 0.69 | 350 | 3.9648 | 0.0472 | 0.0029 | 0.0472 | 0.0054 | 0.3175 |
| No log | 0.78 | 400 | 3.8977 | 0.0553 | 0.0279 | 0.0553 | 0.0164 | 0.3283 |
| No log | 0.88 | 450 | 3.8290 | 0.0768 | 0.0239 | 0.0768 | 0.0230 | 0.3437 |
| No log | 0.98 | 500 | 3.7650 | 0.0701 | 0.0313 | 0.0701 | 0.0252 | 0.3418 |
| 4.166 | 1.08 | 550 | 3.7060 | 0.0997 | 0.0444 | 0.0997 | 0.0418 | 0.3625 |
| 4.166 | 1.18 | 600 | 3.6526 | 0.1132 | 0.0497 | 0.1132 | 0.0501 | 0.3733 |
| 4.166 | 1.27 | 650 | 3.5931 | 0.1132 | 0.0433 | 0.1132 | 0.0509 | 0.3732 |
| 4.166 | 1.37 | 700 | 3.5467 | 0.1240 | 0.0664 | 0.1240 | 0.0558 | 0.3805 |
| 4.166 | 1.47 | 750 | 3.4981 | 0.1213 | 0.0589 | 0.1213 | 0.0553 | 0.3792 |
| 4.166 | 1.57 | 800 | 3.4544 | 0.1361 | 0.0606 | 0.1361 | 0.0641 | 0.3904 |
| 4.166 | 1.67 | 850 | 3.4081 | 0.1456 | 0.0557 | 0.1456 | 0.0655 | 0.3980 |
| 4.166 | 1.76 | 900 | 3.3696 | 0.1536 | 0.0812 | 0.1536 | 0.0786 | 0.4040 |
| 4.166 | 1.86 | 950 | 3.3213 | 0.1523 | 0.0609 | 0.1523 | 0.0745 | 0.4038 |
| 4.166 | 1.96 | 1000 | 3.2814 | 0.1779 | 0.0991 | 0.1779 | 0.0922 | 0.4217 |
| 3.6654 | 2.06 | 1050 | 3.2435 | 0.1550 | 0.0883 | 0.1550 | 0.0737 | 0.4061 |
| 3.6654 | 2.16 | 1100 | 3.2094 | 0.1712 | 0.0867 | 0.1712 | 0.0887 | 0.4166 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.3.0
- Datasets 2.19.1
- Tokenizers 0.15.1
|