Hugging Face's logo

Shijia
/
run1

Text2Text Generation
Transformers
Safetensors
t5
Generated from Trainer
Eval Results
Inference Endpoints
text-generation-inference
Model card Files Community
Shijia commited on
Commit
3135430
•
1 Parent(s): 8a71ef5

Model save

Browse files
Files changed (2) hide show
  1. README.md +23 -33
  2. model.safetensors +1 -1
README.md CHANGED
@@ -1,6 +1,6 @@
1
  ---
2
- license: mit
3
- base_model: emilyalsentzer/Bio_ClinicalBERT
4
  tags:
5
  - generated_from_trainer
6
  datasets:
@@ -25,16 +25,16 @@ model-index:
25
  metrics:
26
  - name: Accuracy
27
  type: accuracy
28
- value: 0.575
29
  - name: Precision
30
  type: precision
31
- value: 0.5800000000000001
32
  - name: Recall
33
  type: recall
34
- value: 0.575
35
  - name: F1
36
  type: f1
37
- value: 0.5682539682539682
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -42,13 +42,13 @@ should probably proofread and complete it, then remove this comment. -->
42
 
43
  # run1
44
 
45
- This model is a fine-tuned version of [emilyalsentzer/Bio_ClinicalBERT](https://huggingface.co/emilyalsentzer/Bio_ClinicalBERT) on the sem_eval_2024_task_2 dataset.
46
  It achieves the following results on the evaluation set:
47
- - Loss: 1.2723
48
- - Accuracy: 0.575
49
- - Precision: 0.5800
50
- - Recall: 0.575
51
- - F1: 0.5683
52
 
53
  ## Model description
54
 
@@ -75,33 +75,23 @@ The following hyperparameters were used during training:
75
  - total_train_batch_size: 32
76
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
77
  - lr_scheduler_type: linear
78
- - num_epochs: 20
79
  - mixed_precision_training: Native AMP
80
 
81
  ### Training results
82
 
83
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
84
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
85
- | No log | 0.99 | 53 | 0.6960 | 0.52 | 0.5339 | 0.52 | 0.4652 |
86
- | 0.7039 | 2.0 | 107 | 0.6921 | 0.545 | 0.5451 | 0.5450 | 0.5447 |
87
- | 0.7039 | 2.99 | 160 | 0.6956 | 0.515 | 0.5436 | 0.515 | 0.4198 |
88
- | 0.6979 | 4.0 | 214 | 0.6857 | 0.555 | 0.5587 | 0.555 | 0.5479 |
89
- | 0.6979 | 4.99 | 267 | 0.6924 | 0.51 | 0.7525 | 0.51 | 0.3552 |
90
- | 0.6831 | 6.0 | 321 | 0.6603 | 0.575 | 0.5750 | 0.575 | 0.5750 |
91
- | 0.6831 | 6.99 | 374 | 0.6572 | 0.61 | 0.6116 | 0.6100 | 0.6086 |
92
- | 0.6346 | 8.0 | 428 | 0.6517 | 0.57 | 0.5700 | 0.5700 | 0.5700 |
93
- | 0.6346 | 8.99 | 481 | 0.7185 | 0.58 | 0.5849 | 0.58 | 0.5739 |
94
- | 0.5337 | 10.0 | 535 | 0.8220 | 0.565 | 0.5767 | 0.565 | 0.5478 |
95
- | 0.5337 | 10.99 | 588 | 0.8002 | 0.595 | 0.5958 | 0.595 | 0.5942 |
96
- | 0.4262 | 12.0 | 642 | 0.8661 | 0.595 | 0.5994 | 0.595 | 0.5905 |
97
- | 0.4262 | 12.99 | 695 | 0.9989 | 0.555 | 0.5608 | 0.5550 | 0.5440 |
98
- | 0.3379 | 14.0 | 749 | 1.0688 | 0.56 | 0.5651 | 0.5600 | 0.5512 |
99
- | 0.3379 | 14.99 | 802 | 1.0439 | 0.585 | 0.5865 | 0.585 | 0.5832 |
100
- | 0.2846 | 16.0 | 856 | 1.1091 | 0.575 | 0.5809 | 0.575 | 0.5671 |
101
- | 0.2846 | 16.99 | 909 | 1.2667 | 0.57 | 0.5791 | 0.5700 | 0.5572 |
102
- | 0.228 | 18.0 | 963 | 1.2367 | 0.58 | 0.5858 | 0.58 | 0.5728 |
103
- | 0.228 | 18.99 | 1016 | 1.2373 | 0.585 | 0.5889 | 0.585 | 0.5804 |
104
- | 0.2137 | 19.81 | 1060 | 1.2723 | 0.575 | 0.5800 | 0.575 | 0.5683 |
105
 
106
 
107
  ### Framework versions
 
1
  ---
2
+ license: apache-2.0
3
+ base_model: michiyasunaga/BioLinkBERT-base
4
  tags:
5
  - generated_from_trainer
6
  datasets:
 
25
  metrics:
26
  - name: Accuracy
27
  type: accuracy
28
+ value: 0.62
29
  - name: Precision
30
  type: precision
31
+ value: 0.6273344651952462
32
  - name: Recall
33
  type: recall
34
+ value: 0.62
35
  - name: F1
36
  type: f1
37
+ value: 0.614448051948052
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
42
 
43
  # run1
44
 
45
+ This model is a fine-tuned version of [michiyasunaga/BioLinkBERT-base](https://huggingface.co/michiyasunaga/BioLinkBERT-base) on the sem_eval_2024_task_2 dataset.
46
  It achieves the following results on the evaluation set:
47
+ - Loss: 0.6923
48
+ - Accuracy: 0.62
49
+ - Precision: 0.6273
50
+ - Recall: 0.62
51
+ - F1: 0.6144
52
 
53
  ## Model description
54
 
 
75
  - total_train_batch_size: 32
76
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
77
  - lr_scheduler_type: linear
78
+ - num_epochs: 10
79
  - mixed_precision_training: Native AMP
80
 
81
  ### Training results
82
 
83
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
84
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
85
+ | No log | 0.99 | 53 | 0.6893 | 0.55 | 0.5565 | 0.55 | 0.5366 |
86
+ | 0.7034 | 2.0 | 107 | 0.6771 | 0.595 | 0.5986 | 0.595 | 0.5913 |
87
+ | 0.7034 | 2.99 | 160 | 0.6680 | 0.585 | 0.5882 | 0.585 | 0.5812 |
88
+ | 0.6769 | 4.0 | 214 | 0.6448 | 0.625 | 0.6271 | 0.625 | 0.6234 |
89
+ | 0.6769 | 4.99 | 267 | 0.6465 | 0.625 | 0.6503 | 0.625 | 0.6085 |
90
+ | 0.5962 | 6.0 | 321 | 0.6457 | 0.635 | 0.6456 | 0.635 | 0.6282 |
91
+ | 0.5962 | 6.99 | 374 | 0.6595 | 0.63 | 0.6366 | 0.63 | 0.6255 |
92
+ | 0.4977 | 8.0 | 428 | 0.6763 | 0.62 | 0.6273 | 0.62 | 0.6144 |
93
+ | 0.4977 | 8.99 | 481 | 0.6831 | 0.63 | 0.6379 | 0.63 | 0.6246 |
94
+ | 0.4268 | 9.91 | 530 | 0.6923 | 0.62 | 0.6273 | 0.62 | 0.6144 |
 
 
 
 
 
 
 
 
 
 
95
 
96
 
97
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:25fdd5cc3634b221352cbc346bcf63e6d1f6b4a338db8ef55e82d996df46cd04
3
  size 432960488
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e2a081ea449c5682a262acc26e3aaeb05f753144160fa2bd97a8d9d6ba28ed27
3
  size 432960488