Hugging Face's logo

stulcrad
/
CNEC2_0_Supertypes_xlm-roberta-large

Token Classification
Transformers
TensorBoard
Safetensors
xlm-roberta
Generated from Trainer
Eval Results
Inference Endpoints
Model card Files Metrics Community
stulcrad commited on
Commit
aaae25c
•
1 Parent(s): 3995095

Model save

Browse files
Files changed (2) hide show
  1. README.md +19 -19
  2. model.safetensors +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
25
  metrics:
26
  - name: Precision
27
  type: precision
28
- value: 0.8074141048824593
29
  - name: Recall
30
  type: recall
31
- value: 0.861969111969112
32
  - name: F1
33
  type: f1
34
- value: 0.8338001867413634
35
  - name: Accuracy
36
  type: accuracy
37
- value: 0.9655222367086774
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
44
 
45
  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
46
  It achieves the following results on the evaluation set:
47
- - Loss: 0.2044
48
- - Precision: 0.8074
49
- - Recall: 0.8620
50
- - F1: 0.8338
51
- - Accuracy: 0.9655
52
 
53
  ## Model description
54
 
@@ -67,7 +67,7 @@ More information needed
67
  ### Training hyperparameters
68
 
69
  The following hyperparameters were used during training:
70
- - learning_rate: 5e-05
71
  - train_batch_size: 16
72
  - eval_batch_size: 16
73
  - seed: 42
@@ -81,15 +81,15 @@ The following hyperparameters were used during training:
81
 
82
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
83
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
84
- | 0.5564 | 1.11 | 500 | 0.1852 | 0.6302 | 0.7558 | 0.6873 | 0.9502 |
85
- | 0.1786 | 2.22 | 1000 | 0.1552 | 0.6952 | 0.8069 | 0.7469 | 0.9568 |
86
- | 0.1219 | 3.33 | 1500 | 0.1665 | 0.6860 | 0.8214 | 0.7476 | 0.9577 |
87
- | 0.087 | 4.44 | 2000 | 0.1616 | 0.7572 | 0.8263 | 0.7902 | 0.9595 |
88
- | 0.0689 | 5.56 | 2500 | 0.1679 | 0.7670 | 0.8243 | 0.7946 | 0.9616 |
89
- | 0.0442 | 6.67 | 3000 | 0.1612 | 0.7346 | 0.8364 | 0.7822 | 0.9631 |
90
- | 0.0353 | 7.78 | 3500 | 0.1864 | 0.8099 | 0.8576 | 0.8331 | 0.9653 |
91
- | 0.0205 | 8.89 | 4000 | 0.1950 | 0.8026 | 0.8653 | 0.8328 | 0.9654 |
92
- | 0.0133 | 10.0 | 4500 | 0.2044 | 0.8074 | 0.8620 | 0.8338 | 0.9655 |
93
 
94
 
95
  ### Framework versions
 
25
  metrics:
26
  - name: Precision
27
  type: precision
28
+ value: 0.8375401560348784
29
  - name: Recall
30
  type: recall
31
+ value: 0.8807915057915058
32
  - name: F1
33
  type: f1
34
+ value: 0.8586215008233357
35
  - name: Accuracy
36
  type: accuracy
37
+ value: 0.9697233087063596
38
  ---
39
 
40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
44
 
45
  This model is a fine-tuned version of [FacebookAI/xlm-roberta-large](https://huggingface.co/FacebookAI/xlm-roberta-large) on the cnec dataset.
46
  It achieves the following results on the evaluation set:
47
+ - Loss: 0.1726
48
+ - Precision: 0.8375
49
+ - Recall: 0.8808
50
+ - F1: 0.8586
51
+ - Accuracy: 0.9697
52
 
53
  ## Model description
54
 
 
67
  ### Training hyperparameters
68
 
69
  The following hyperparameters were used during training:
70
+ - learning_rate: 2e-05
71
  - train_batch_size: 16
72
  - eval_batch_size: 16
73
  - seed: 42
 
81
 
82
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
83
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
84
+ | 0.6046 | 1.11 | 500 | 0.1815 | 0.6422 | 0.7693 | 0.7000 | 0.9498 |
85
+ | 0.1671 | 2.22 | 1000 | 0.1389 | 0.7436 | 0.8456 | 0.7913 | 0.9620 |
86
+ | 0.1141 | 3.33 | 1500 | 0.1455 | 0.7949 | 0.8813 | 0.8359 | 0.9686 |
87
+ | 0.0854 | 4.44 | 2000 | 0.1455 | 0.8012 | 0.8678 | 0.8332 | 0.9684 |
88
+ | 0.0716 | 5.56 | 2500 | 0.1418 | 0.7996 | 0.8663 | 0.8316 | 0.9682 |
89
+ | 0.0506 | 6.67 | 3000 | 0.1570 | 0.8138 | 0.8793 | 0.8453 | 0.9690 |
90
+ | 0.0399 | 7.78 | 3500 | 0.1701 | 0.8363 | 0.8803 | 0.8577 | 0.9689 |
91
+ | 0.0324 | 8.89 | 4000 | 0.1720 | 0.8313 | 0.8798 | 0.8549 | 0.9691 |
92
+ | 0.0265 | 10.0 | 4500 | 0.1726 | 0.8375 | 0.8808 | 0.8586 | 0.9697 |
93
 
94
 
95
  ### Framework versions
model.safetensors CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:21cfd131b6823894abd4de5fd5bfdbf487188276f587fc57d664bbe723cffa8c
3
  size 2235481556
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:44487d696f986dad6126e2c464c096dbfaf0abaad4d563ca27b6a54db93088e8
3
  size 2235481556