Commit
•
6b66793
1
Parent(s):
d3b97f8
update model card README.md
Browse files
README.md
ADDED
|
@@ -0,0 +1,79 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
---
|
| 2 |
+
license: mit
|
| 3 |
+
tags:
|
| 4 |
+
- generated_from_trainer
|
| 5 |
+
metrics:
|
| 6 |
+
- precision
|
| 7 |
+
- recall
|
| 8 |
+
- f1
|
| 9 |
+
- accuracy
|
| 10 |
+
model-index:
|
| 11 |
+
- name: group1_non_all_zero
|
| 12 |
+
results: []
|
| 13 |
+
---
|
| 14 |
+
|
| 15 |
+
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
|
| 16 |
+
should probably proofread and complete it, then remove this comment. -->
|
| 17 |
+
|
| 18 |
+
# group1_non_all_zero
|
| 19 |
+
|
| 20 |
+
This model is a fine-tuned version of [microsoft/deberta-v3-base](https://huggingface.co/microsoft/deberta-v3-base) on an unknown dataset.
|
| 21 |
+
It achieves the following results on the evaluation set:
|
| 22 |
+
- Loss: 0.7437
|
| 23 |
+
- Precision: 0.0149
|
| 24 |
+
- Recall: 0.1076
|
| 25 |
+
- F1: 0.0262
|
| 26 |
+
- Accuracy: 0.9260
|
| 27 |
+
|
| 28 |
+
## Model description
|
| 29 |
+
|
| 30 |
+
More information needed
|
| 31 |
+
|
| 32 |
+
## Intended uses & limitations
|
| 33 |
+
|
| 34 |
+
More information needed
|
| 35 |
+
|
| 36 |
+
## Training and evaluation data
|
| 37 |
+
|
| 38 |
+
More information needed
|
| 39 |
+
|
| 40 |
+
## Training procedure
|
| 41 |
+
|
| 42 |
+
### Training hyperparameters
|
| 43 |
+
|
| 44 |
+
The following hyperparameters were used during training:
|
| 45 |
+
- learning_rate: 3e-05
|
| 46 |
+
- train_batch_size: 32
|
| 47 |
+
- eval_batch_size: 32
|
| 48 |
+
- seed: 42
|
| 49 |
+
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
|
| 50 |
+
- lr_scheduler_type: linear
|
| 51 |
+
- num_epochs: 15
|
| 52 |
+
|
| 53 |
+
### Training results
|
| 54 |
+
|
| 55 |
+
| Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
|
| 56 |
+
|:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
|
| 57 |
+
| No log | 1.0 | 15 | 1.0746 | 0.0007 | 0.0633 | 0.0013 | 0.4145 |
|
| 58 |
+
| No log | 2.0 | 30 | 0.8623 | 0.0023 | 0.1139 | 0.0045 | 0.6250 |
|
| 59 |
+
| No log | 3.0 | 45 | 0.7242 | 0.0024 | 0.0696 | 0.0046 | 0.7334 |
|
| 60 |
+
| No log | 4.0 | 60 | 0.6181 | 0.0037 | 0.0696 | 0.0070 | 0.8030 |
|
| 61 |
+
| No log | 5.0 | 75 | 0.6489 | 0.0090 | 0.1329 | 0.0169 | 0.8282 |
|
| 62 |
+
| No log | 6.0 | 90 | 0.6538 | 0.0091 | 0.1266 | 0.0170 | 0.8445 |
|
| 63 |
+
| No log | 7.0 | 105 | 0.6189 | 0.0103 | 0.1013 | 0.0188 | 0.8893 |
|
| 64 |
+
| No log | 8.0 | 120 | 0.6328 | 0.0101 | 0.1013 | 0.0183 | 0.8917 |
|
| 65 |
+
| No log | 9.0 | 135 | 0.6561 | 0.0119 | 0.1076 | 0.0215 | 0.9099 |
|
| 66 |
+
| No log | 10.0 | 150 | 0.6537 | 0.0152 | 0.1139 | 0.0267 | 0.9265 |
|
| 67 |
+
| No log | 11.0 | 165 | 0.6939 | 0.0182 | 0.1139 | 0.0314 | 0.9385 |
|
| 68 |
+
| No log | 12.0 | 180 | 0.7481 | 0.0113 | 0.0949 | 0.0203 | 0.9103 |
|
| 69 |
+
| No log | 13.0 | 195 | 0.7242 | 0.0150 | 0.1203 | 0.0267 | 0.9209 |
|
| 70 |
+
| No log | 14.0 | 210 | 0.7553 | 0.0140 | 0.1013 | 0.0247 | 0.9229 |
|
| 71 |
+
| No log | 15.0 | 225 | 0.7437 | 0.0149 | 0.1076 | 0.0262 | 0.9260 |
|
| 72 |
+
|
| 73 |
+
|
| 74 |
+
### Framework versions
|
| 75 |
+
|
| 76 |
+
- Transformers 4.30.0
|
| 77 |
+
- Pytorch 2.2.2+cu121
|
| 78 |
+
- Datasets 2.19.0
|
| 79 |
+
- Tokenizers 0.13.3
|