Hugging Face's logo

mnavas
/
roberta-finetuned-WebClassification-v2-smalllinguaENv2

Text Classification
Transformers
PyTorch
TensorBoard
roberta
Generated from Trainer
Model card Files Metrics Community
2
María Navas Loro commited on
Commit
2cc7a57
·
1 Parent(s): 818c435

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +15 -15
README.md CHANGED
@@ -19,11 +19,11 @@ should probably proofread and complete it, then remove this comment. -->
19
 
20
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
- - Loss: 1.8560
23
- - Accuracy: 0.525
24
- - F1: 0.525
25
- - Precision: 0.525
26
- - Recall: 0.525
27
 
28
  ## Model description
29
 
@@ -54,16 +54,16 @@ The following hyperparameters were used during training:
54
 
55
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
56
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
57
- | No log | 1.0 | 20 | 2.9637 | 0.1 | 0.1000 | 0.1 | 0.1 |
58
- | No log | 2.0 | 40 | 2.7821 | 0.225 | 0.225 | 0.225 | 0.225 |
59
- | No log | 3.0 | 60 | 2.5523 | 0.4 | 0.4000 | 0.4 | 0.4 |
60
- | No log | 4.0 | 80 | 2.3580 | 0.4 | 0.4000 | 0.4 | 0.4 |
61
- | No log | 5.0 | 100 | 2.2043 | 0.375 | 0.375 | 0.375 | 0.375 |
62
- | No log | 6.0 | 120 | 2.0265 | 0.475 | 0.4750 | 0.475 | 0.475 |
63
- | No log | 7.0 | 140 | 1.9271 | 0.5 | 0.5 | 0.5 | 0.5 |
64
- | No log | 8.0 | 160 | 1.8560 | 0.525 | 0.525 | 0.525 | 0.525 |
65
- | No log | 9.0 | 180 | 1.8013 | 0.525 | 0.525 | 0.525 | 0.525 |
66
- | No log | 10.0 | 200 | 1.7784 | 0.525 | 0.525 | 0.525 | 0.525 |
67
 
68
 
69
  ### Framework versions
 
19
 
20
  This model is a fine-tuned version of [xlm-roberta-base](https://huggingface.co/xlm-roberta-base) on the None dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 1.7384
23
+ - Accuracy: 0.55
24
+ - F1: 0.55
25
+ - Precision: 0.55
26
+ - Recall: 0.55
27
 
28
  ## Model description
29
 
 
54
 
55
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | F1 | Precision | Recall |
56
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:------:|:---------:|:------:|
57
+ | No log | 1.0 | 20 | 2.9187 | 0.075 | 0.075 | 0.075 | 0.075 |
58
+ | No log | 2.0 | 40 | 2.8030 | 0.15 | 0.15 | 0.15 | 0.15 |
59
+ | No log | 3.0 | 60 | 2.6273 | 0.325 | 0.325 | 0.325 | 0.325 |
60
+ | No log | 4.0 | 80 | 2.3371 | 0.45 | 0.45 | 0.45 | 0.45 |
61
+ | No log | 5.0 | 100 | 2.1233 | 0.425 | 0.425 | 0.425 | 0.425 |
62
+ | No log | 6.0 | 120 | 1.9737 | 0.525 | 0.525 | 0.525 | 0.525 |
63
+ | No log | 7.0 | 140 | 1.8962 | 0.475 | 0.4750 | 0.475 | 0.475 |
64
+ | No log | 8.0 | 160 | 1.8013 | 0.525 | 0.525 | 0.525 | 0.525 |
65
+ | No log | 9.0 | 180 | 1.7384 | 0.55 | 0.55 | 0.55 | 0.55 |
66
+ | No log | 10.0 | 200 | 1.7237 | 0.55 | 0.55 | 0.55 | 0.55 |
67
 
68
 
69
  ### Framework versions