Hugging Face's logo

avsolatorio
/
doc-topic-model_eval-04_train-03

Text Classification
Transformers
Safetensors
deberta-v2
Generated from Trainer
Inference Endpoints
Model card Files Community
avsolatorio commited on
Commit
1aed8cf
•
1 Parent(s): 8006133

avsolatorio/doc-topic-model_eval-04_train-03

Browse files
Files changed (2) hide show
  1. README.md +83 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,83 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ library_name: transformers
3
+ license: mit
4
+ base_model: microsoft/deberta-v3-small
5
+ tags:
6
+ - generated_from_trainer
7
+ metrics:
8
+ - accuracy
9
+ - f1
10
+ - precision
11
+ - recall
12
+ model-index:
13
+ - name: doc-topic-model_eval-04_train-03
14
+ results: []
15
+ ---
16
+
17
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
18
+ should probably proofread and complete it, then remove this comment. -->
19
+
20
+ # doc-topic-model_eval-04_train-03
21
+
22
+ This model is a fine-tuned version of [microsoft/deberta-v3-small](https://huggingface.co/microsoft/deberta-v3-small) on an unknown dataset.
23
+ It achieves the following results on the evaluation set:
24
+ - Loss: 0.0378
25
+ - Accuracy: 0.9878
26
+ - F1: 0.6242
27
+ - Precision: 0.7287
28
+ - Recall: 0.5459
29
+
30
+ ## Model description
31
+
32
+ More information needed
33
+
34
+ ## Intended uses & limitations
35
+
36
+ More information needed
37
+
38
+ ## Training and evaluation data
39
+
40
+ More information needed
41
+
42
+ ## Training procedure
43
+
44
+ ### Training hyperparameters
45
+
46
+ The following hyperparameters were used during training:
47
+ - learning_rate: 2e-05
48
+ - train_batch_size: 4
49
+ - eval_batch_size: 256
50
+ - seed: 42
51
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
52
+ - lr_scheduler_type: linear
53
+ - num_epochs: 100
54
+ - mixed_precision_training: Native AMP
55
+
56
+ ### Training results
57
+
58
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
59
+ |:-------------:|:------:|:-----:|:---------------:|:--------:|:------:|:---------:|:------:|
60
+ | 0.0935 | 0.4931 | 1000 | 0.0894 | 0.9815 | 0.0 | 0.0 | 0.0 |
61
+ | 0.0764 | 0.9862 | 2000 | 0.0699 | 0.9815 | 0.0 | 0.0 | 0.0 |
62
+ | 0.0621 | 1.4793 | 3000 | 0.0567 | 0.9821 | 0.0732 | 0.8832 | 0.0382 |
63
+ | 0.0542 | 1.9724 | 4000 | 0.0495 | 0.9840 | 0.2881 | 0.8175 | 0.1749 |
64
+ | 0.0468 | 2.4655 | 5000 | 0.0465 | 0.9854 | 0.4302 | 0.7764 | 0.2975 |
65
+ | 0.0441 | 2.9586 | 6000 | 0.0433 | 0.9861 | 0.4928 | 0.7613 | 0.3643 |
66
+ | 0.0395 | 3.4517 | 7000 | 0.0415 | 0.9862 | 0.5333 | 0.7144 | 0.4254 |
67
+ | 0.0384 | 3.9448 | 8000 | 0.0397 | 0.9868 | 0.5643 | 0.7222 | 0.4631 |
68
+ | 0.0343 | 4.4379 | 9000 | 0.0389 | 0.9870 | 0.5808 | 0.7188 | 0.4873 |
69
+ | 0.0337 | 4.9310 | 10000 | 0.0376 | 0.9875 | 0.5954 | 0.7393 | 0.4985 |
70
+ | 0.0305 | 5.4241 | 11000 | 0.0371 | 0.9876 | 0.6006 | 0.7449 | 0.5032 |
71
+ | 0.0295 | 5.9172 | 12000 | 0.0375 | 0.9876 | 0.6106 | 0.7257 | 0.5270 |
72
+ | 0.0271 | 6.4103 | 13000 | 0.0371 | 0.9878 | 0.6096 | 0.7493 | 0.5138 |
73
+ | 0.0257 | 6.9034 | 14000 | 0.0373 | 0.9878 | 0.6171 | 0.7325 | 0.5332 |
74
+ | 0.0234 | 7.3964 | 15000 | 0.0373 | 0.9877 | 0.6277 | 0.7127 | 0.5609 |
75
+ | 0.0241 | 7.8895 | 16000 | 0.0378 | 0.9878 | 0.6242 | 0.7287 | 0.5459 |
76
+
77
+
78
+ ### Framework versions
79
+
80
+ - Transformers 4.44.2
81
+ - Pytorch 2.4.1+cu121
82
+ - Datasets 2.21.0
83
+ - Tokenizers 0.19.1
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:08617865067656e4e06231828eda918e8826650a2df85095a7f188ce116a569f
3
  size 567860028
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:a14ba6d631b491aedf133a76099b0070972351da82405b18ac3450de34336449
3
  size 567860028