Hugging Face's logo

Tirendaz
/
roberta-base-NER

Token Classification
Transformers
PyTorch
English
xlm-roberta
Eval Results
Inference Endpoints
Model card Files Community
Tirendaz commited on
Commit
271d883
•
1 Parent(s): 53baeb4

End of training

Browse files
Files changed (2) hide show
  1. README.md +15 -13
  2. pytorch_model.bin +1 -1
README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
25
  metrics:
26
  - name: Precision
27
  type: precision
28
- value: 0.7779299014238773
29
  - name: Recall
30
  type: recall
31
- value: 0.8005071851225697
32
  - name: F1
33
  type: f1
34
- value: 0.7890570754061935
35
  - name: Accuracy
36
  type: accuracy
37
- value: 0.912818107767877
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 [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
46
  It achieves the following results on the evaluation set:
47
- - Loss: 0.2988
48
- - Precision: 0.7779
49
- - Recall: 0.8005
50
- - F1: 0.7891
51
- - Accuracy: 0.9128
52
 
53
  ## Model description
54
 
@@ -73,15 +73,17 @@ The following hyperparameters were used during training:
73
  - seed: 42
74
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
75
  - lr_scheduler_type: linear
76
- - num_epochs: 3
77
 
78
  ### Training results
79
 
80
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
81
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
82
- | No log | 1.0 | 417 | 0.3344 | 0.7337 | 0.7732 | 0.7529 | 0.9019 |
83
- | 0.5039 | 2.0 | 834 | 0.2995 | 0.7588 | 0.7932 | 0.7756 | 0.9104 |
84
- | 0.2841 | 3.0 | 1251 | 0.2988 | 0.7779 | 0.8005 | 0.7891 | 0.9128 |
 
 
85
 
86
 
87
  ### Framework versions
 
25
  metrics:
26
  - name: Precision
27
  type: precision
28
+ value: 0.8003614625330182
29
  - name: Recall
30
  type: recall
31
+ value: 0.8110735418427726
32
  - name: F1
33
  type: f1
34
+ value: 0.8056818976978517
35
  - name: Accuracy
36
  type: accuracy
37
+ value: 0.9194332683336213
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 [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the xtreme dataset.
46
  It achieves the following results on the evaluation set:
47
+ - Loss: 0.2935
48
+ - Precision: 0.8004
49
+ - Recall: 0.8111
50
+ - F1: 0.8057
51
+ - Accuracy: 0.9194
52
 
53
  ## Model description
54
 
 
73
  - seed: 42
74
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
75
  - lr_scheduler_type: linear
76
+ - num_epochs: 5
77
 
78
  ### Training results
79
 
80
  | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
81
  |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
82
+ | No log | 1.0 | 417 | 0.3359 | 0.7286 | 0.7675 | 0.7476 | 0.8991 |
83
+ | 0.4227 | 2.0 | 834 | 0.2951 | 0.7711 | 0.7980 | 0.7843 | 0.9131 |
84
+ | 0.2818 | 3.0 | 1251 | 0.2824 | 0.7852 | 0.8076 | 0.7962 | 0.9174 |
85
+ | 0.2186 | 4.0 | 1668 | 0.2853 | 0.7934 | 0.8150 | 0.8041 | 0.9193 |
86
+ | 0.1801 | 5.0 | 2085 | 0.2935 | 0.8004 | 0.8111 | 0.8057 | 0.9194 |
87
 
88
 
89
  ### Framework versions
pytorch_model.bin CHANGED
@@ -1,3 +1,3 @@
1
  version https://git-lfs.github.com/spec/v1
2
- oid sha256:d31b520406a5294df3270a9eaca8118875e656d528e683aaaddedc2ee5bbc991
3
  size 1109902057
 
1
  version https://git-lfs.github.com/spec/v1
2
+ oid sha256:e8701935667229a1b5d43eea1ed268b151d3aa1a5ce8154f277b55a8766a4790
3
  size 1109902057