update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,72 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: apache-2.0
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- accuracy
|
| 7 |
+
- precision
|
| 8 |
+
- recall
|
| 9 |
+
model-index:
|
| 10 |
+
- name: distilbert-base-uncased-PINA
|
| 11 |
+
results: []
|
| 12 |
+
---
|
| 13 |
+
|
| 14 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 15 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 16 |
+
|
| 17 |
+
# distilbert-base-uncased-PINA
|
| 18 |
+
|
| 19 |
+
This model is a fine-tuned version of [distilbert-base-uncased](https://huggingface.co/distilbert-base-uncased) on the None dataset.
|
| 20 |
+
It achieves the following results on the evaluation set:
|
| 21 |
+
- Loss: 1.0745
|
| 22 |
+
- Accuracy: 0.7628
|
| 23 |
+
- Precision: 0.5795
|
| 24 |
+
- Recall: 0.5194
|
| 25 |
+
|
| 26 |
+
## Model description
|
| 27 |
+
|
| 28 |
+
More information needed
|
| 29 |
+
|
| 30 |
+
## Intended uses & limitations
|
| 31 |
+
|
| 32 |
+
More information needed
|
| 33 |
+
|
| 34 |
+
## Training and evaluation data
|
| 35 |
+
|
| 36 |
+
More information needed
|
| 37 |
+
|
| 38 |
+
## Training procedure
|
| 39 |
+
|
| 40 |
+
### Training hyperparameters
|
| 41 |
+
|
| 42 |
+
The following hyperparameters were used during training:
|
| 43 |
+
- learning_rate: 2e-05
|
| 44 |
+
- train_batch_size: 16
|
| 45 |
+
- eval_batch_size: 16
|
| 46 |
+
- seed: 42
|
| 47 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 48 |
+
- lr_scheduler_type: linear
|
| 49 |
+
- num_epochs: 10
|
| 50 |
+
|
| 51 |
+
### Training results
|
| 52 |
+
|
| 53 |
+
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|
| 54 |
+
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
|
| 55 |
+
| 2.591 | 1.0 | 234 | 2.2068 | 0.4444 | 0.0523 | 0.0477 |
|
| 56 |
+
| 1.9869 | 2.0 | 468 | 1.7959 | 0.5876 | 0.2023 | 0.1887 |
|
| 57 |
+
| 1.5443 | 3.0 | 702 | 1.5389 | 0.6378 | 0.2921 | 0.2857 |
|
| 58 |
+
| 1.2084 | 4.0 | 936 | 1.3623 | 0.6848 | 0.3983 | 0.3562 |
|
| 59 |
+
| 0.9397 | 5.0 | 1170 | 1.2348 | 0.7244 | 0.4999 | 0.4112 |
|
| 60 |
+
| 0.7445 | 6.0 | 1404 | 1.1657 | 0.7286 | 0.5053 | 0.4481 |
|
| 61 |
+
| 0.6204 | 7.0 | 1638 | 1.1167 | 0.7564 | 0.5773 | 0.4918 |
|
| 62 |
+
| 0.5183 | 8.0 | 1872 | 1.0872 | 0.7607 | 0.5841 | 0.5078 |
|
| 63 |
+
| 0.4468 | 9.0 | 2106 | 1.0782 | 0.7628 | 0.5785 | 0.5172 |
|
| 64 |
+
| 0.4188 | 10.0 | 2340 | 1.0745 | 0.7628 | 0.5795 | 0.5194 |
|
| 65 |
+
|
| 66 |
+
|
| 67 |
+
### Framework versions
|
| 68 |
+
|
| 69 |
+
- Transformers 4.27.4
|
| 70 |
+
- Pytorch 2.0.0+cu118
|
| 71 |
+
- Datasets 2.11.0
|
| 72 |
+
- Tokenizers 0.13.2
|