Hugging Face's logo

Shijia
/
run1

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
Eval Results
text-generation-inference
Inference Endpoints
Model card Files Community
Shijia commited on
Commit
d7aeae0
•
1 Parent(s): ba4fc39

Model save

Browse files
Files changed (2) hide show
  1. README.md +111 -0
  2. model.safetensors +1 -1
README.md ADDED
@@ -0,0 +1,111 @@
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
1
+ ---
2
+ base_model: medicalai/ClinicalBERT
3
+ tags:
4
+ - generated_from_trainer
5
+ datasets:
6
+ - sem_eval_2024_task_2
7
+ metrics:
8
+ - accuracy
9
+ - precision
10
+ - recall
11
+ - f1
12
+ model-index:
13
+ - name: run1
14
+ results:
15
+ - task:
16
+ name: Text Classification
17
+ type: text-classification
18
+ dataset:
19
+ name: sem_eval_2024_task_2
20
+ type: sem_eval_2024_task_2
21
+ config: sem_eval_2024_task_2_source
22
+ split: validation
23
+ args: sem_eval_2024_task_2_source
24
+ metrics:
25
+ - name: Accuracy
26
+ type: accuracy
27
+ value: 0.595
28
+ - name: Precision
29
+ type: precision
30
+ value: 0.632109581421221
31
+ - name: Recall
32
+ type: recall
33
+ value: 0.595
34
+ - name: F1
35
+ type: f1
36
+ value: 0.5644107445349681
37
+ ---
38
+
39
+ <!-- This model card has been generated automatically according to the information the Trainer had access to. You
40
+ should probably proofread and complete it, then remove this comment. -->
41
+
42
+ # run1
43
+
44
+ This model is a fine-tuned version of [medicalai/ClinicalBERT](https://huggingface.co/medicalai/ClinicalBERT) on the sem_eval_2024_task_2 dataset.
45
+ It achieves the following results on the evaluation set:
46
+ - Loss: 0.6989
47
+ - Accuracy: 0.595
48
+ - Precision: 0.6321
49
+ - Recall: 0.595
50
+ - F1: 0.5644
51
+
52
+ ## Model description
53
+
54
+ More information needed
55
+
56
+ ## Intended uses & limitations
57
+
58
+ More information needed
59
+
60
+ ## Training and evaluation data
61
+
62
+ More information needed
63
+
64
+ ## Training procedure
65
+
66
+ ### Training hyperparameters
67
+
68
+ The following hyperparameters were used during training:
69
+ - learning_rate: 2e-05
70
+ - train_batch_size: 16
71
+ - eval_batch_size: 64
72
+ - seed: 42
73
+ - gradient_accumulation_steps: 2
74
+ - total_train_batch_size: 32
75
+ - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
76
+ - lr_scheduler_type: linear
77
+ - num_epochs: 20
78
+ - mixed_precision_training: Native AMP
79
+
80
+ ### Training results
81
+
82
+ | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
83
+ |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
84
+ | No log | 0.99 | 53 | 0.6932 | 0.5 | 0.5 | 0.5 | 0.4302 |
85
+ | 0.6952 | 2.0 | 107 | 0.6946 | 0.505 | 0.5059 | 0.505 | 0.4854 |
86
+ | 0.6952 | 2.99 | 160 | 0.6938 | 0.485 | 0.4127 | 0.485 | 0.3505 |
87
+ | 0.6953 | 4.0 | 214 | 0.6937 | 0.5 | 0.5 | 0.5 | 0.4389 |
88
+ | 0.6953 | 4.99 | 267 | 0.6961 | 0.5 | 0.25 | 0.5 | 0.3333 |
89
+ | 0.6937 | 6.0 | 321 | 0.6936 | 0.5 | 0.25 | 0.5 | 0.3333 |
90
+ | 0.6937 | 6.99 | 374 | 0.6908 | 0.495 | 0.4487 | 0.495 | 0.3479 |
91
+ | 0.6927 | 8.0 | 428 | 0.6804 | 0.545 | 0.5485 | 0.545 | 0.5366 |
92
+ | 0.6927 | 8.99 | 481 | 0.6888 | 0.525 | 0.5535 | 0.525 | 0.4520 |
93
+ | 0.6799 | 10.0 | 535 | 0.6657 | 0.615 | 0.6476 | 0.615 | 0.5925 |
94
+ | 0.6799 | 10.99 | 588 | 0.6600 | 0.625 | 0.6448 | 0.625 | 0.6117 |
95
+ | 0.6509 | 12.0 | 642 | 0.6598 | 0.595 | 0.6407 | 0.595 | 0.5592 |
96
+ | 0.6509 | 12.99 | 695 | 0.6598 | 0.605 | 0.6555 | 0.605 | 0.5701 |
97
+ | 0.6122 | 14.0 | 749 | 0.6643 | 0.59 | 0.6234 | 0.59 | 0.5603 |
98
+ | 0.6122 | 14.99 | 802 | 0.6754 | 0.605 | 0.6818 | 0.605 | 0.5584 |
99
+ | 0.5601 | 16.0 | 856 | 0.6788 | 0.605 | 0.6382 | 0.605 | 0.5798 |
100
+ | 0.5601 | 16.99 | 909 | 0.6864 | 0.59 | 0.6234 | 0.59 | 0.5603 |
101
+ | 0.5159 | 18.0 | 963 | 0.6967 | 0.6 | 0.6457 | 0.6 | 0.5660 |
102
+ | 0.5159 | 18.99 | 1016 | 0.7037 | 0.6 | 0.6507 | 0.6 | 0.5633 |
103
+ | 0.5117 | 19.81 | 1060 | 0.6989 | 0.595 | 0.6321 | 0.595 | 0.5644 |
104
+
105
+
106
+ ### Framework versions
107
+
108
+ - Transformers 4.35.2
109
+ - Pytorch 2.1.0+cu121
110
+ - Datasets 2.15.0
111
+ - Tokenizers 0.15.0
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:26215c5f1f9ceb93e19c814ae42ded3f3aa17d3bb701341ee413f306619d7a5b
3
  size 541317368
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e6cadef33911d1a16c26d2d953053ed7bea60e4a4f23bd9a948aac00c1ce4f71
3
  size 541317368