Hugging Face's logo

poltextlab
/
xlm-roberta-large-german-cap

Text Classification
Transformers
PyTorch
German
xlm-roberta
zero-shot-classification
Inference Endpoints
Model card Files Community
1
poltextlab commited on
Commit
38c4d78
•
1 Parent(s): 2534ff0

Upload README.md with huggingface_hub

Browse files
Files changed (1) hide show
  1. README.md +26 -25
README.md CHANGED
@@ -90,33 +90,34 @@ training_args = TrainingArguments(
90
  We also incorporated an EarlyStoppingCallback in the process with a patience of 2 epochs.
91
 
92
  ## Model performance
93
- The model was evaluated on a test set of 482 examples (10% of the available data).<br>
94
- Model accuracy is **0.6**.
95
  | label | precision | recall | f1-score | support |
96
  |:-------------|------------:|---------:|-----------:|----------:|
97
- | 0 | 0.51 | 0.61 | 0.55 | 38 |
98
- | 1 | 0.25 | 0.07 | 0.11 | 14 |
99
- | 2 | 0.57 | 0.73 | 0.64 | 11 |
100
- | 3 | 0.4 | 0.5 | 0.44 | 8 |
101
- | 4 | 0.64 | 0.54 | 0.58 | 13 |
102
- | 5 | 0.33 | 0.33 | 0.33 | 3 |
103
- | 6 | 0 | 0 | 0 | 3 |
104
- | 7 | 0.67 | 0.67 | 0.67 | 6 |
105
- | 8 | 0.75 | 0.6 | 0.67 | 10 |
106
- | 9 | 0.78 | 0.75 | 0.76 | 28 |
107
- | 10 | 0.2 | 0.06 | 0.1 | 16 |
108
- | 11 | 0.67 | 0.5 | 0.57 | 4 |
109
- | 12 | 0 | 0 | 0 | 3 |
110
- | 13 | 0.48 | 0.37 | 0.42 | 27 |
111
- | 14 | 0.7 | 0.62 | 0.65 | 78 |
112
- | 15 | 0.25 | 0.25 | 0.25 | 4 |
113
- | 16 | 0 | 0 | 0 | 8 |
114
- | 17 | 0.58 | 0.69 | 0.63 | 105 |
115
- | 18 | 0.62 | 0.79 | 0.7 | 97 |
116
- | 19 | 0 | 0 | 0 | 1 |
117
- | 20 | 1 | 0.6 | 0.75 | 5 |
118
- | macro avg | 0.45 | 0.41 | 0.42 | 482 |
119
- | weighted avg | 0.57 | 0.6 | 0.58 | 482 |
 
120
 
121
  ## Inference platform
122
  This model is used by the [CAP Babel Machine](https://babel.poltextlab.com), an open-source and free natural language processing tool, designed to simplify and speed up projects for comparative research.
 
90
  We also incorporated an EarlyStoppingCallback in the process with a patience of 2 epochs.
91
 
92
  ## Model performance
93
+ The model was evaluated on a test set of 5227 examples (10% of the available data).<br>
94
+ Model accuracy is **0.7**.
95
  | label | precision | recall | f1-score | support |
96
  |:-------------|------------:|---------:|-----------:|----------:|
97
+ | 0 | 0.62 | 0.65 | 0.63 | 510 |
98
+ | 1 | 0.73 | 0.67 | 0.7 | 406 |
99
+ | 2 | 0.8 | 0.83 | 0.81 | 239 |
100
+ | 3 | 0.75 | 0.78 | 0.76 | 136 |
101
+ | 4 | 0.72 | 0.65 | 0.68 | 386 |
102
+ | 5 | 0.79 | 0.82 | 0.81 | 331 |
103
+ | 6 | 0.76 | 0.65 | 0.7 | 264 |
104
+ | 7 | 0.81 | 0.79 | 0.8 | 189 |
105
+ | 8 | 0.8 | 0.8 | 0.8 | 121 |
106
+ | 9 | 0.78 | 0.83 | 0.81 | 151 |
107
+ | 10 | 0.72 | 0.66 | 0.69 | 304 |
108
+ | 11 | 0.67 | 0.67 | 0.67 | 452 |
109
+ | 12 | 0.68 | 0.72 | 0.7 | 184 |
110
+ | 13 | 0.54 | 0.64 | 0.59 | 269 |
111
+ | 14 | 0.78 | 0.7 | 0.74 | 212 |
112
+ | 15 | 0.63 | 0.77 | 0.69 | 154 |
113
+ | 16 | 0.53 | 0.57 | 0.55 | 61 |
114
+ | 17 | 0.75 | 0.71 | 0.73 | 471 |
115
+ | 18 | 0.62 | 0.62 | 0.62 | 301 |
116
+ | 19 | 0.27 | 0.5 | 0.35 | 8 |
117
+ | 20 | 0.79 | 0.82 | 0.81 | 78 |
118
+ | 21 | 0 | 0 | 0 | 0 |
119
+ | macro avg | 0.66 | 0.68 | 0.67 | 5227 |
120
+ | weighted avg | 0.71 | 0.7 | 0.7 | 5227 |
121
 
122
  ## Inference platform
123
  This model is used by the [CAP Babel Machine](https://babel.poltextlab.com), an open-source and free natural language processing tool, designed to simplify and speed up projects for comparative research.