domenicrosati commited on
Commit
c2eac86
1 Parent(s): d020fa8

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +65 -0
README.md ADDED
@@ -0,0 +1,65 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ license: mit
3
+ tags:
4
+ - text-classification
5
+ - generated_from_trainer
6
+ metrics:
7
+ - accuracy
8
+ - f1
9
+ model-index:
10
+ - name: deberta-v3-xsmall-finetuned-review_classifier
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
+ # deberta-v3-xsmall-finetuned-review_classifier
18
+
19
+ This model is a fine-tuned version of [microsoft/deberta-v3-xsmall](https://huggingface.co/microsoft/deberta-v3-xsmall) on an unknown dataset.
20
+ It achieves the following results on the evaluation set:
21
+ - Loss: 0.1441
22
+ - Accuracy: 0.9513
23
+ - F1: 0.7458
24
+
25
+ ## Model description
26
+
27
+ More information needed
28
+
29
+ ## Intended uses & limitations
30
+
31
+ More information needed
32
+
33
+ ## Training and evaluation data
34
+
35
+ More information needed
36
+
37
+ ## Training procedure
38
+
39
+ ### Training hyperparameters
40
+
41
+ The following hyperparameters were used during training:
42
+ - learning_rate: 4.5e-05
43
+ - train_batch_size: 12
44
+ - eval_batch_size: 12
45
+ - seed: 42
46
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
47
+ - lr_scheduler_type: linear
48
+ - lr_scheduler_warmup_steps: 1000
49
+ - num_epochs: 2
50
+ - mixed_precision_training: Native AMP
51
+
52
+ ### Training results
53
+
54
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 |
55
+ |:-------------:|:-----:|:-----:|:---------------:|:--------:|:------:|
56
+ | 0.1518 | 1.0 | 6667 | 0.1575 | 0.9510 | 0.7155 |
57
+ | 0.1247 | 2.0 | 13334 | 0.1441 | 0.9513 | 0.7458 |
58
+
59
+
60
+ ### Framework versions
61
+
62
+ - Transformers 4.20.1
63
+ - Pytorch 1.11.0+cu113
64
+ - Datasets 2.3.2
65
+ - Tokenizers 0.12.1