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fine_tuned_mBERT

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mehdie/fine_tuned_mBERT

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  2. model.safetensors +1 -1
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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 [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
- - Loss: 0.1592
23
- - F1: 0.7805
24
- - F5: 0.8186
25
- - Precision: 0.6957
26
- - Recall: 0.8889
27
 
28
  ## Model description
29
 
@@ -43,26 +43,27 @@ More information needed
43
 
44
  The following hyperparameters were used during training:
45
  - learning_rate: 5e-05
46
- - train_batch_size: 256
47
- - eval_batch_size: 256
48
  - seed: 42
49
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
  - lr_scheduler_type: linear
51
- - num_epochs: 8
52
  - mixed_precision_training: Native AMP
53
 
54
  ### Training results
55
 
56
  | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
57
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
58
- | No log | 1.0 | 6 | 0.3289 | 0.0 | 0.0 | 0.0 | 0.0 |
59
- | No log | 2.0 | 12 | 0.3095 | 0.0 | 0.0 | 0.0 | 0.0 |
60
- | No log | 3.0 | 18 | 0.2680 | 0.3636 | 0.2925 | 1.0 | 0.2222 |
61
- | No log | 4.0 | 24 | 0.2876 | 0.4 | 0.3424 | 0.7143 | 0.2778 |
62
- | No log | 5.0 | 30 | 0.2680 | 0.6087 | 0.6638 | 0.5 | 0.7778 |
63
- | No log | 6.0 | 36 | 0.2565 | 0.4615 | 0.4024 | 0.75 | 0.3333 |
64
- | No log | 7.0 | 42 | 0.2320 | 0.6341 | 0.6651 | 0.5652 | 0.7222 |
65
- | No log | 8.0 | 48 | 0.2251 | 0.6 | 0.5574 | 0.75 | 0.5 |
 
66
 
67
 
68
  ### Framework versions
 
19
 
20
  This model is a fine-tuned version of [google-bert/bert-base-multilingual-cased](https://huggingface.co/google-bert/bert-base-multilingual-cased) on an unknown dataset.
21
  It achieves the following results on the evaluation set:
22
+ - Loss: 0.0788
23
+ - F1: 0.8387
24
+ - F5: 0.8492
25
+ - Precision: 0.8125
26
+ - Recall: 0.8667
27
 
28
  ## Model description
29
 
 
43
 
44
  The following hyperparameters were used during training:
45
  - learning_rate: 5e-05
46
+ - train_batch_size: 128
47
+ - eval_batch_size: 128
48
  - seed: 42
49
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
50
  - lr_scheduler_type: linear
51
+ - num_epochs: 9
52
  - mixed_precision_training: Native AMP
53
 
54
  ### Training results
55
 
56
  | Training Loss | Epoch | Step | Validation Loss | F1 | F5 | Precision | Recall |
57
  |:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:---------:|:------:|
58
+ | No log | 1.0 | 11 | 0.2709 | 0.0 | 0.0 | 0.0 | 0.0 |
59
+ | No log | 2.0 | 22 | 0.2130 | 0.1333 | 0.1002 | 1.0 | 0.0714 |
60
+ | No log | 3.0 | 33 | 0.1537 | 0.6207 | 0.6290 | 0.6 | 0.6429 |
61
+ | No log | 4.0 | 44 | 0.0986 | 0.7200 | 0.6884 | 0.8182 | 0.6429 |
62
+ | No log | 5.0 | 55 | 0.1376 | 0.7333 | 0.7525 | 0.6875 | 0.7857 |
63
+ | No log | 6.0 | 66 | 0.1490 | 0.6207 | 0.6290 | 0.6 | 0.6429 |
64
+ | No log | 7.0 | 77 | 0.1969 | 0.64 | 0.6120 | 0.7273 | 0.5714 |
65
+ | No log | 8.0 | 88 | 0.2131 | 0.6897 | 0.6989 | 0.6667 | 0.7143 |
66
+ | No log | 9.0 | 99 | 0.2097 | 0.6154 | 0.5978 | 0.6667 | 0.5714 |
67
 
68
 
69
  ### Framework versions
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