Hugging Face's logo

mfreihaut
/
refinement-finetuned-mnli-1

Text Classification
Transformers
PyTorch
bart
Generated from Trainer
Model card Files
xet
Community
1
mfreihaut commited on
Commit
7e5dcb7
·
1 Parent(s): f709780

update model card README.md

Browse files
Files changed (1) hide show
  1. README.md +53 -28
README.md CHANGED
@@ -12,9 +12,9 @@ should probably proofread and complete it, then remove this comment. -->
12
 
13
  # refinement-finetuned-mnli-1
14
 
15
- This model is a fine-tuned version of [facebook/bart-large-mnli](https://huggingface.co/facebook/bart-large-mnli) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
- - Loss: 0.0000
18
 
19
  ## Model description
20
 
@@ -39,37 +39,62 @@ The following hyperparameters were used during training:
39
  - seed: 42
40
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
41
  - lr_scheduler_type: linear
42
- - num_epochs: 25
43
 
44
  ### Training results
45
 
46
  | Training Loss | Epoch | Step | Validation Loss |
47
  |:-------------:|:-----:|:----:|:---------------:|
48
- | No log | 1.0 | 25 | 0.0000 |
49
- | No log | 2.0 | 50 | 0.0000 |
50
- | No log | 3.0 | 75 | 0.0000 |
51
- | No log | 4.0 | 100 | 0.0000 |
52
- | No log | 5.0 | 125 | 0.0000 |
53
- | No log | 6.0 | 150 | 0.0000 |
54
- | No log | 7.0 | 175 | 0.0000 |
55
- | No log | 8.0 | 200 | 0.0000 |
56
- | No log | 9.0 | 225 | 0.0000 |
57
- | No log | 10.0 | 250 | 0.0000 |
58
- | No log | 11.0 | 275 | 0.0000 |
59
- | No log | 12.0 | 300 | 0.0000 |
60
- | No log | 13.0 | 325 | 0.0000 |
61
- | No log | 14.0 | 350 | 0.0000 |
62
- | No log | 15.0 | 375 | 0.0000 |
63
- | No log | 16.0 | 400 | 0.0000 |
64
- | No log | 17.0 | 425 | 0.0000 |
65
- | No log | 18.0 | 450 | 0.0000 |
66
- | No log | 19.0 | 475 | 0.0000 |
67
- | 0.0056 | 20.0 | 500 | 0.0000 |
68
- | 0.0056 | 21.0 | 525 | 0.0000 |
69
- | 0.0056 | 22.0 | 550 | 0.0000 |
70
- | 0.0056 | 23.0 | 575 | 0.0000 |
71
- | 0.0056 | 24.0 | 600 | 0.0000 |
72
- | 0.0056 | 25.0 | 625 | 0.0000 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
73
 
74
 
75
  ### Framework versions
 
12
 
13
  # refinement-finetuned-mnli-1
14
 
15
+ This model is a fine-tuned version of [mfreihaut/refinement-finetuned-mnli-1](https://huggingface.co/mfreihaut/refinement-finetuned-mnli-1) on the None dataset.
16
  It achieves the following results on the evaluation set:
17
+ - Loss: 6.9744
18
 
19
  ## Model description
20
 
 
39
  - seed: 42
40
  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
41
  - lr_scheduler_type: linear
42
+ - num_epochs: 50
43
 
44
  ### Training results
45
 
46
  | Training Loss | Epoch | Step | Validation Loss |
47
  |:-------------:|:-----:|:----:|:---------------:|
48
+ | No log | 1.0 | 50 | 3.6639 |
49
+ | No log | 2.0 | 100 | 3.1760 |
50
+ | No log | 3.0 | 150 | 3.5147 |
51
+ | No log | 4.0 | 200 | 7.2978 |
52
+ | No log | 5.0 | 250 | 6.9823 |
53
+ | No log | 6.0 | 300 | 6.1548 |
54
+ | No log | 7.0 | 350 | 1.8893 |
55
+ | No log | 8.0 | 400 | 3.4601 |
56
+ | No log | 9.0 | 450 | 5.1852 |
57
+ | 0.9791 | 10.0 | 500 | 5.1913 |
58
+ | 0.9791 | 11.0 | 550 | 2.7786 |
59
+ | 0.9791 | 12.0 | 600 | 6.8241 |
60
+ | 0.9791 | 13.0 | 650 | 5.2724 |
61
+ | 0.9791 | 14.0 | 700 | 4.7973 |
62
+ | 0.9791 | 15.0 | 750 | 6.1139 |
63
+ | 0.9791 | 16.0 | 800 | 6.5590 |
64
+ | 0.9791 | 17.0 | 850 | 5.6065 |
65
+ | 0.9791 | 18.0 | 900 | 6.4056 |
66
+ | 0.9791 | 19.0 | 950 | 5.7737 |
67
+ | 0.3292 | 20.0 | 1000 | 5.6033 |
68
+ | 0.3292 | 21.0 | 1050 | 6.8969 |
69
+ | 0.3292 | 22.0 | 1100 | 6.3766 |
70
+ | 0.3292 | 23.0 | 1150 | 6.1115 |
71
+ | 0.3292 | 24.0 | 1200 | 6.3750 |
72
+ | 0.3292 | 25.0 | 1250 | 6.3604 |
73
+ | 0.3292 | 26.0 | 1300 | 6.4051 |
74
+ | 0.3292 | 27.0 | 1350 | 6.7069 |
75
+ | 0.3292 | 28.0 | 1400 | 6.3017 |
76
+ | 0.3292 | 29.0 | 1450 | 6.9539 |
77
+ | 0.2482 | 30.0 | 1500 | 6.9133 |
78
+ | 0.2482 | 31.0 | 1550 | 6.5188 |
79
+ | 0.2482 | 32.0 | 1600 | 6.7478 |
80
+ | 0.2482 | 33.0 | 1650 | 6.5621 |
81
+ | 0.2482 | 34.0 | 1700 | 6.9490 |
82
+ | 0.2482 | 35.0 | 1750 | 6.6875 |
83
+ | 0.2482 | 36.0 | 1800 | 6.7723 |
84
+ | 0.2482 | 37.0 | 1850 | 6.5755 |
85
+ | 0.2482 | 38.0 | 1900 | 6.8727 |
86
+ | 0.2482 | 39.0 | 1950 | 6.8581 |
87
+ | 0.2245 | 40.0 | 2000 | 6.9993 |
88
+ | 0.2245 | 41.0 | 2050 | 7.1120 |
89
+ | 0.2245 | 42.0 | 2100 | 7.2491 |
90
+ | 0.2245 | 43.0 | 2150 | 7.0870 |
91
+ | 0.2245 | 44.0 | 2200 | 7.3960 |
92
+ | 0.2245 | 45.0 | 2250 | 7.0658 |
93
+ | 0.2245 | 46.0 | 2300 | 7.0175 |
94
+ | 0.2245 | 47.0 | 2350 | 7.0082 |
95
+ | 0.2245 | 48.0 | 2400 | 6.9570 |
96
+ | 0.2245 | 49.0 | 2450 | 6.9720 |
97
+ | 0.2124 | 50.0 | 2500 | 6.9744 |
98
 
99
 
100
  ### Framework versions