update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,80 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
- f1
|
| 8 |
+
model-index:
|
| 9 |
+
- name: verizon_model1
|
| 10 |
+
results: []
|
| 11 |
+
---
|
| 12 |
+
|
| 13 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 14 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 15 |
+
|
| 16 |
+
# verizon_model1
|
| 17 |
+
|
| 18 |
+
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on an unknown dataset.
|
| 19 |
+
It achieves the following results on the evaluation set:
|
| 20 |
+
- Loss: 0.0752
|
| 21 |
+
- Accuracy: 0.9804
|
| 22 |
+
- F1: 0.9797
|
| 23 |
+
|
| 24 |
+
## Model description
|
| 25 |
+
|
| 26 |
+
More information needed
|
| 27 |
+
|
| 28 |
+
## Intended uses & limitations
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Training and evaluation data
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training procedure
|
| 37 |
+
|
| 38 |
+
### Training hyperparameters
|
| 39 |
+
|
| 40 |
+
The following hyperparameters were used during training:
|
| 41 |
+
- learning_rate: 2e-05
|
| 42 |
+
- train_batch_size: 64
|
| 43 |
+
- eval_batch_size: 64
|
| 44 |
+
- seed: 42
|
| 45 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 46 |
+
- lr_scheduler_type: linear
|
| 47 |
+
- num_epochs: 20
|
| 48 |
+
|
| 49 |
+
### Training results
|
| 50 |
+
|
| 51 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
|
| 52 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|
|
| 53 |
+
| 1.5222 | 1.0 | 8 | 1.4173 | 0.5686 | 0.5681 |
|
| 54 |
+
| 1.2748 | 2.0 | 16 | 1.1744 | 0.7647 | 0.6850 |
|
| 55 |
+
| 1.0552 | 3.0 | 24 | 0.9130 | 0.7843 | 0.7001 |
|
| 56 |
+
| 0.8588 | 4.0 | 32 | 0.6877 | 0.8824 | 0.8290 |
|
| 57 |
+
| 0.6473 | 5.0 | 40 | 0.5120 | 0.8824 | 0.8291 |
|
| 58 |
+
| 0.5048 | 6.0 | 48 | 0.3791 | 0.9216 | 0.9049 |
|
| 59 |
+
| 0.3041 | 7.0 | 56 | 0.2843 | 0.9804 | 0.9797 |
|
| 60 |
+
| 0.2355 | 8.0 | 64 | 0.2135 | 0.9804 | 0.9797 |
|
| 61 |
+
| 0.2168 | 9.0 | 72 | 0.1657 | 0.9804 | 0.9797 |
|
| 62 |
+
| 0.1318 | 10.0 | 80 | 0.1408 | 0.9804 | 0.9797 |
|
| 63 |
+
| 0.1205 | 11.0 | 88 | 0.1167 | 0.9804 | 0.9797 |
|
| 64 |
+
| 0.0858 | 12.0 | 96 | 0.1037 | 0.9804 | 0.9797 |
|
| 65 |
+
| 0.0968 | 13.0 | 104 | 0.0954 | 0.9804 | 0.9797 |
|
| 66 |
+
| 0.0658 | 14.0 | 112 | 0.0894 | 0.9804 | 0.9797 |
|
| 67 |
+
| 0.0655 | 15.0 | 120 | 0.0828 | 0.9804 | 0.9797 |
|
| 68 |
+
| 0.0581 | 16.0 | 128 | 0.0794 | 0.9804 | 0.9797 |
|
| 69 |
+
| 0.0612 | 17.0 | 136 | 0.0786 | 0.9804 | 0.9797 |
|
| 70 |
+
| 0.059 | 18.0 | 144 | 0.0767 | 0.9804 | 0.9797 |
|
| 71 |
+
| 0.0512 | 19.0 | 152 | 0.0756 | 0.9804 | 0.9797 |
|
| 72 |
+
| 0.0479 | 20.0 | 160 | 0.0752 | 0.9804 | 0.9797 |
|
| 73 |
+
|
| 74 |
+
|
| 75 |
+
### Framework versions
|
| 76 |
+
|
| 77 |
+
- Transformers 4.16.2
|
| 78 |
+
- Pytorch 2.1.0+cu121
|
| 79 |
+
- Datasets 2.18.0
|
| 80 |
+
- Tokenizers 0.15.2
|