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my_awesome_wnut_model

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  1. README.md +95 -25
  2. config.json +1 -1
  3. model.safetensors +2 -2
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README.md CHANGED
@@ -1,7 +1,7 @@
1
  ---
2
  library_name: transformers
3
  license: apache-2.0
4
- base_model: sentence-transformers/all-MiniLM-L6-v2
5
  tags:
6
  - generated_from_trainer
7
  metrics:
@@ -19,13 +19,13 @@ should probably proofread and complete it, then remove this comment. -->
19
 
20
  # my_awesome_wnut_model
21
 
22
- This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L6-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L6-v2) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
- - Loss: 0.8907
25
- - Precision: 0.0
26
- - Recall: 0.0
27
- - F1: 0.0
28
- - Accuracy: 0.8995
29
 
30
  ## Model description
31
 
@@ -44,33 +44,103 @@ More information needed
44
  ### Training hyperparameters
45
 
46
  The following hyperparameters were used during training:
47
- - learning_rate: 2e-06
48
- - train_batch_size: 128
49
- - eval_batch_size: 128
50
  - seed: 42
51
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
52
  - lr_scheduler_type: linear
53
- - num_epochs: 10
54
 
55
  ### Training results
56
 
57
- | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
58
- |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:---:|:--------:|
59
- | No log | 1.0 | 5 | 1.0442 | 0.0 | 0.0 | 0.0 | 0.7738 |
60
- | No log | 2.0 | 10 | 1.0181 | 0.0 | 0.0 | 0.0 | 0.8208 |
61
- | No log | 3.0 | 15 | 0.9938 | 0.0 | 0.0 | 0.0 | 0.8437 |
62
- | No log | 4.0 | 20 | 0.9709 | 0.0 | 0.0 | 0.0 | 0.8601 |
63
- | No log | 5.0 | 25 | 0.9496 | 0.0 | 0.0 | 0.0 | 0.8719 |
64
- | No log | 6.0 | 30 | 0.9306 | 0.0 | 0.0 | 0.0 | 0.8836 |
65
- | No log | 7.0 | 35 | 0.9143 | 0.0 | 0.0 | 0.0 | 0.8915 |
66
- | No log | 8.0 | 40 | 0.9018 | 0.0 | 0.0 | 0.0 | 0.8958 |
67
- | No log | 9.0 | 45 | 0.8938 | 0.0 | 0.0 | 0.0 | 0.8986 |
68
- | No log | 10.0 | 50 | 0.8907 | 0.0 | 0.0 | 0.0 | 0.8995 |
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
69
 
70
 
71
  ### Framework versions
72
 
73
  - Transformers 4.53.2
74
- - Pytorch 2.6.0+cu124
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- - Datasets 2.14.4
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  - Tokenizers 0.21.2
 
1
  ---
2
  library_name: transformers
3
  license: apache-2.0
4
+ base_model: sentence-transformers/all-MiniLM-L12-v2
5
  tags:
6
  - generated_from_trainer
7
  metrics:
 
19
 
20
  # my_awesome_wnut_model
21
 
22
+ This model is a fine-tuned version of [sentence-transformers/all-MiniLM-L12-v2](https://huggingface.co/sentence-transformers/all-MiniLM-L12-v2) on the None dataset.
23
  It achieves the following results on the evaluation set:
24
+ - Loss: 0.2159
25
+ - Precision: 0.5140
26
+ - Recall: 0.4074
27
+ - F1: 0.4545
28
+ - Accuracy: 0.9695
29
 
30
  ## Model description
31
 
 
44
  ### Training hyperparameters
45
 
46
  The following hyperparameters were used during training:
47
+ - learning_rate: 0.0002
48
+ - train_batch_size: 64
49
+ - eval_batch_size: 64
50
  - seed: 42
51
  - optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
52
  - lr_scheduler_type: linear
53
+ - num_epochs: 40
54
 
55
  ### Training results
56
 
57
+ | Training Loss | Epoch | Step | Validation Loss | Precision | Recall | F1 | Accuracy |
58
+ |:-------------:|:-----:|:----:|:---------------:|:---------:|:------:|:------:|:--------:|
59
+ | 0.1888 | 0.5 | 5 | 0.2202 | 0.0 | 0.0 | 0.0 | 0.9446 |
60
+ | 0.1751 | 1.0 | 10 | 0.1946 | 0.0 | 0.0 | 0.0 | 0.9452 |
61
+ | 0.1339 | 1.5 | 15 | 0.2030 | 0.0226 | 0.0815 | 0.0354 | 0.9244 |
62
+ | 0.1044 | 2.0 | 20 | 0.1600 | 0.0735 | 0.1333 | 0.0947 | 0.9562 |
63
+ | 0.1438 | 2.5 | 25 | 0.1427 | 0.1657 | 0.2222 | 0.1899 | 0.9611 |
64
+ | 0.0631 | 3.0 | 30 | 0.1341 | 0.25 | 0.2 | 0.2222 | 0.9644 |
65
+ | 0.0908 | 3.5 | 35 | 0.1356 | 0.0989 | 0.0667 | 0.0796 | 0.9639 |
66
+ | 0.0899 | 4.0 | 40 | 0.1322 | 0.3077 | 0.2370 | 0.2678 | 0.9665 |
67
+ | 0.0772 | 4.5 | 45 | 0.1376 | 0.3113 | 0.2444 | 0.2739 | 0.9673 |
68
+ | 0.1036 | 5.0 | 50 | 0.1200 | 0.2909 | 0.2370 | 0.2612 | 0.9678 |
69
+ | 0.103 | 5.5 | 55 | 0.1278 | 0.3008 | 0.2963 | 0.2985 | 0.9681 |
70
+ | 0.0233 | 6.0 | 60 | 0.1288 | 0.2756 | 0.2593 | 0.2672 | 0.9694 |
71
+ | 0.0564 | 6.5 | 65 | 0.1251 | 0.2391 | 0.2444 | 0.2418 | 0.9696 |
72
+ | 0.0693 | 7.0 | 70 | 0.1397 | 0.2562 | 0.3037 | 0.2780 | 0.9637 |
73
+ | 0.0652 | 7.5 | 75 | 0.1390 | 0.3310 | 0.3481 | 0.3394 | 0.9645 |
74
+ | 0.099 | 8.0 | 80 | 0.1215 | 0.3810 | 0.2963 | 0.3333 | 0.9691 |
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+ | 0.0493 | 8.5 | 85 | 0.1480 | 0.3571 | 0.2963 | 0.3239 | 0.9667 |
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+ | 0.0587 | 9.0 | 90 | 0.1481 | 0.2981 | 0.3556 | 0.3243 | 0.9621 |
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+ | 0.0611 | 9.5 | 95 | 0.1407 | 0.4167 | 0.2593 | 0.3196 | 0.9698 |
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+ | 0.0365 | 10.0 | 100 | 0.1605 | 0.3721 | 0.3556 | 0.3636 | 0.9655 |
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+ | 0.0489 | 10.5 | 105 | 0.1505 | 0.3805 | 0.3185 | 0.3468 | 0.9680 |
80
+ | 0.0562 | 11.0 | 110 | 0.1605 | 0.3289 | 0.3704 | 0.3484 | 0.9618 |
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+ | 0.0666 | 11.5 | 115 | 0.1568 | 0.3898 | 0.3407 | 0.3636 | 0.9702 |
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+ | 0.0294 | 12.0 | 120 | 0.1552 | 0.4643 | 0.3852 | 0.4211 | 0.9702 |
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+ | 0.0577 | 12.5 | 125 | 0.1682 | 0.4407 | 0.3852 | 0.4111 | 0.9668 |
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+ | 0.035 | 13.0 | 130 | 0.1687 | 0.4835 | 0.3259 | 0.3894 | 0.9712 |
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+ | 0.064 | 13.5 | 135 | 0.1619 | 0.4463 | 0.4 | 0.4219 | 0.9662 |
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+ | 0.0423 | 14.0 | 140 | 0.1673 | 0.5455 | 0.3556 | 0.4305 | 0.9718 |
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+ | 0.0589 | 14.5 | 145 | 0.1939 | 0.4286 | 0.3778 | 0.4016 | 0.9656 |
88
+ | 0.0728 | 15.0 | 150 | 0.1695 | 0.4333 | 0.3852 | 0.4078 | 0.9667 |
89
+ | 0.0533 | 15.5 | 155 | 0.1723 | 0.4273 | 0.3481 | 0.3837 | 0.9706 |
90
+ | 0.0333 | 16.0 | 160 | 0.1932 | 0.4180 | 0.3778 | 0.3969 | 0.9667 |
91
+ | 0.0413 | 16.5 | 165 | 0.1789 | 0.4486 | 0.3556 | 0.3967 | 0.9704 |
92
+ | 0.0437 | 17.0 | 170 | 0.1927 | 0.4732 | 0.3926 | 0.4291 | 0.9669 |
93
+ | 0.0588 | 17.5 | 175 | 0.1945 | 0.4690 | 0.3926 | 0.4274 | 0.9674 |
94
+ | 0.0621 | 18.0 | 180 | 0.1984 | 0.4955 | 0.4074 | 0.4472 | 0.9676 |
95
+ | 0.0413 | 18.5 | 185 | 0.2025 | 0.4016 | 0.3778 | 0.3893 | 0.9686 |
96
+ | 0.0586 | 19.0 | 190 | 0.1827 | 0.4054 | 0.3333 | 0.3659 | 0.9708 |
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+ | 0.06 | 19.5 | 195 | 0.1956 | 0.4231 | 0.4074 | 0.4151 | 0.9684 |
98
+ | 0.0775 | 20.0 | 200 | 0.1974 | 0.5521 | 0.3926 | 0.4589 | 0.9722 |
99
+ | 0.0508 | 20.5 | 205 | 0.2081 | 0.4655 | 0.4 | 0.4303 | 0.9672 |
100
+ | 0.0317 | 21.0 | 210 | 0.1941 | 0.5319 | 0.3704 | 0.4367 | 0.9727 |
101
+ | 0.0373 | 21.5 | 215 | 0.2012 | 0.52 | 0.3852 | 0.4426 | 0.9715 |
102
+ | 0.0314 | 22.0 | 220 | 0.1935 | 0.5444 | 0.3630 | 0.4356 | 0.9724 |
103
+ | 0.0471 | 22.5 | 225 | 0.2048 | 0.408 | 0.3778 | 0.3923 | 0.9675 |
104
+ | 0.0287 | 23.0 | 230 | 0.1944 | 0.5 | 0.3852 | 0.4351 | 0.9695 |
105
+ | 0.0598 | 23.5 | 235 | 0.2008 | 0.4911 | 0.4074 | 0.4453 | 0.9683 |
106
+ | 0.0336 | 24.0 | 240 | 0.2114 | 0.4867 | 0.4074 | 0.4435 | 0.9661 |
107
+ | 0.0406 | 24.5 | 245 | 0.1988 | 0.5368 | 0.3778 | 0.4435 | 0.9717 |
108
+ | 0.0761 | 25.0 | 250 | 0.2126 | 0.4167 | 0.4074 | 0.4120 | 0.9673 |
109
+ | 0.0484 | 25.5 | 255 | 0.2033 | 0.5543 | 0.3778 | 0.4493 | 0.9716 |
110
+ | 0.0488 | 26.0 | 260 | 0.2034 | 0.5258 | 0.3778 | 0.4397 | 0.9716 |
111
+ | 0.0483 | 26.5 | 265 | 0.2096 | 0.5093 | 0.4074 | 0.4527 | 0.9706 |
112
+ | 0.052 | 27.0 | 270 | 0.2088 | 0.5050 | 0.3778 | 0.4322 | 0.9718 |
113
+ | 0.0454 | 27.5 | 275 | 0.2143 | 0.5046 | 0.4074 | 0.4508 | 0.9677 |
114
+ | 0.0683 | 28.0 | 280 | 0.2110 | 0.4737 | 0.4 | 0.4337 | 0.9700 |
115
+ | 0.0532 | 28.5 | 285 | 0.2111 | 0.4696 | 0.4 | 0.432 | 0.9709 |
116
+ | 0.0427 | 29.0 | 290 | 0.2105 | 0.5567 | 0.4 | 0.4655 | 0.9720 |
117
+ | 0.0407 | 29.5 | 295 | 0.2138 | 0.4909 | 0.4 | 0.4408 | 0.9688 |
118
+ | 0.0346 | 30.0 | 300 | 0.2147 | 0.5047 | 0.4 | 0.4463 | 0.9687 |
119
+ | 0.0562 | 30.5 | 305 | 0.2159 | 0.4909 | 0.4 | 0.4408 | 0.9685 |
120
+ | 0.0455 | 31.0 | 310 | 0.2138 | 0.4696 | 0.4 | 0.432 | 0.9695 |
121
+ | 0.0437 | 31.5 | 315 | 0.2155 | 0.5 | 0.4 | 0.4444 | 0.9687 |
122
+ | 0.0236 | 32.0 | 320 | 0.2130 | 0.4655 | 0.4 | 0.4303 | 0.9708 |
123
+ | 0.0318 | 32.5 | 325 | 0.2139 | 0.4655 | 0.4 | 0.4303 | 0.9708 |
124
+ | 0.0735 | 33.0 | 330 | 0.2169 | 0.4867 | 0.4074 | 0.4435 | 0.9693 |
125
+ | 0.042 | 33.5 | 335 | 0.2183 | 0.4696 | 0.4 | 0.432 | 0.9684 |
126
+ | 0.0588 | 34.0 | 340 | 0.2123 | 0.5684 | 0.4 | 0.4696 | 0.9723 |
127
+ | 0.0461 | 34.5 | 345 | 0.2115 | 0.5047 | 0.4 | 0.4463 | 0.9718 |
128
+ | 0.0786 | 35.0 | 350 | 0.2138 | 0.5094 | 0.4 | 0.4481 | 0.9696 |
129
+ | 0.0323 | 35.5 | 355 | 0.2150 | 0.5093 | 0.4074 | 0.4527 | 0.9690 |
130
+ | 0.048 | 36.0 | 360 | 0.2139 | 0.5140 | 0.4074 | 0.4545 | 0.9696 |
131
+ | 0.0412 | 36.5 | 365 | 0.2141 | 0.5046 | 0.4074 | 0.4508 | 0.9697 |
132
+ | 0.0649 | 37.0 | 370 | 0.2147 | 0.5140 | 0.4074 | 0.4545 | 0.9695 |
133
+ | 0.0506 | 37.5 | 375 | 0.2159 | 0.4955 | 0.4074 | 0.4472 | 0.9687 |
134
+ | 0.0401 | 38.0 | 380 | 0.2168 | 0.5093 | 0.4074 | 0.4527 | 0.9684 |
135
+ | 0.0451 | 38.5 | 385 | 0.2155 | 0.5 | 0.4074 | 0.4490 | 0.9693 |
136
+ | 0.0579 | 39.0 | 390 | 0.2158 | 0.5140 | 0.4074 | 0.4545 | 0.9695 |
137
+ | 0.0565 | 39.5 | 395 | 0.2156 | 0.5140 | 0.4074 | 0.4545 | 0.9695 |
138
+ | 0.0194 | 40.0 | 400 | 0.2159 | 0.5140 | 0.4074 | 0.4545 | 0.9695 |
139
 
140
 
141
  ### Framework versions
142
 
143
  - Transformers 4.53.2
144
+ - Pytorch 2.7.1+cu126
145
+ - Datasets 4.0.0
146
  - Tokenizers 0.21.2
config.json CHANGED
@@ -24,7 +24,7 @@
24
  "max_position_embeddings": 512,
25
  "model_type": "bert",
26
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27
- "num_hidden_layers": 6,
28
  "pad_token_id": 0,
29
  "position_embedding_type": "absolute",
30
  "torch_dtype": "float32",
 
24
  "max_position_embeddings": 512,
25
  "model_type": "bert",
26
  "num_attention_heads": 12,
27
+ "num_hidden_layers": 12,
28
  "pad_token_id": 0,
29
  "position_embedding_type": "absolute",
30
  "torch_dtype": "float32",
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