Commit
•
0da2bb9
1
Parent(s):
deca514
Upload README.md
Browse files
README.md
CHANGED
|
@@ -1,151 +1,213 @@
|
|
|
|
|
| 1 |
---
|
| 2 |
-
|
| 3 |
-
|
|
|
|
| 4 |
tags:
|
|
|
|
|
|
|
| 5 |
- generated_from_trainer
|
| 6 |
-
|
| 7 |
-
- accuracy
|
| 8 |
model-index:
|
| 9 |
- name: drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze
|
| 10 |
results: []
|
| 11 |
---
|
| 12 |
|
| 13 |
-
|
| 14 |
-
should probably proofread and complete it, then remove this comment. -->
|
| 15 |
|
| 16 |
-
# drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze
|
| 17 |
|
| 18 |
-
This model is a fine-tuned version of [facebook/dinov2-large](https://huggingface.co/facebook/dinov2-large) on the None dataset.
|
| 19 |
-
It achieves the following results on the evaluation set:
|
| 20 |
- Loss: 0.2854
|
| 21 |
- F1 Micro: 0.8468
|
| 22 |
- F1 Macro: 0.6351
|
| 23 |
- Accuracy: 0.2786
|
| 24 |
-
- Learning Rate: 0.0000
|
| 25 |
|
| 26 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 27 |
|
| 28 |
-
|
| 29 |
|
| 30 |
-
|
|
|
|
| 31 |
|
| 32 |
-
|
| 33 |
|
| 34 |
-
|
|
|
|
|
|
|
| 35 |
|
| 36 |
-
|
|
|
|
| 37 |
|
| 38 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 39 |
|
| 40 |
-
|
|
|
|
|
|
|
| 41 |
|
| 42 |
The following hyperparameters were used during training:
|
| 43 |
-
|
| 44 |
-
-
|
| 45 |
-
-
|
| 46 |
-
-
|
| 47 |
-
-
|
| 48 |
-
-
|
| 49 |
-
-
|
| 50 |
-
-
|
| 51 |
-
|
| 52 |
-
|
| 53 |
-
|
| 54 |
-
|
| 55 |
-
|
| 56 |
-
|
| 57 |
-
|
| 58 |
-
|
| 59 |
-
|
| 60 |
-
|
| 61 |
-
|
| 62 |
-
|
| 63 |
-
|
| 64 |
-
|
| 65 |
-
|
| 66 |
-
|
| 67 |
-
|
| 68 |
-
|
| 69 |
-
|
| 70 |
-
|
| 71 |
-
|
| 72 |
-
|
| 73 |
-
|
| 74 |
-
|
| 75 |
-
|
| 76 |
-
| 0.
|
| 77 |
-
| 0.
|
| 78 |
-
| 0.
|
| 79 |
-
| 0.
|
| 80 |
-
| 0.
|
| 81 |
-
| 0.
|
| 82 |
-
| 0.
|
| 83 |
-
| 0.
|
| 84 |
-
| 0.
|
| 85 |
-
| 0.
|
| 86 |
-
| 0.
|
| 87 |
-
| 0.
|
| 88 |
-
| 0.
|
| 89 |
-
| 0.
|
| 90 |
-
| 0.
|
| 91 |
-
| 0.
|
| 92 |
-
| 0.
|
| 93 |
-
| 0.
|
| 94 |
-
| 0.
|
| 95 |
-
| 0.
|
| 96 |
-
| 0.
|
| 97 |
-
| 0.
|
| 98 |
-
| 0.
|
| 99 |
-
| 0.
|
| 100 |
-
| 0.
|
| 101 |
-
| 0.
|
| 102 |
-
| 0.
|
| 103 |
-
| 0.
|
| 104 |
-
| 0.
|
| 105 |
-
| 0.
|
| 106 |
-
| 0.
|
| 107 |
-
| 0.
|
| 108 |
-
| 0.
|
| 109 |
-
| 0.
|
| 110 |
-
| 0.
|
| 111 |
-
| 0.
|
| 112 |
-
| 0.
|
| 113 |
-
| 0.
|
| 114 |
-
| 0.
|
| 115 |
-
| 0.
|
| 116 |
-
| 0.
|
| 117 |
-
| 0.
|
| 118 |
-
| 0.
|
| 119 |
-
| 0.
|
| 120 |
-
| 0.
|
| 121 |
-
| 0.
|
| 122 |
-
| 0.
|
| 123 |
-
| 0.
|
| 124 |
-
| 0.
|
| 125 |
-
| 0.
|
| 126 |
-
| 0.
|
| 127 |
-
| 0.
|
| 128 |
-
| 0.
|
| 129 |
-
| 0.
|
| 130 |
-
| 0.
|
| 131 |
-
| 0.
|
| 132 |
-
| 0.
|
| 133 |
-
| 0.
|
| 134 |
-
| 0.
|
| 135 |
-
| 0.
|
| 136 |
-
| 0.
|
| 137 |
-
| 0.
|
| 138 |
-
| 0.
|
| 139 |
-
| 0.
|
| 140 |
-
| 0.
|
| 141 |
-
| 0.
|
| 142 |
-
| 0.
|
| 143 |
-
| 0.
|
| 144 |
-
|
| 145 |
-
|
| 146 |
-
|
| 147 |
-
|
| 148 |
-
|
| 149 |
-
|
| 150 |
-
|
| 151 |
-
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
+
|
| 2 |
---
|
| 3 |
+
language:
|
| 4 |
+
- eng
|
| 5 |
+
license: cc0-1.0
|
| 6 |
tags:
|
| 7 |
+
- multilabel-image-classification
|
| 8 |
+
- multilabel
|
| 9 |
- generated_from_trainer
|
| 10 |
+
base_model: drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze
|
|
|
|
| 11 |
model-index:
|
| 12 |
- name: drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze
|
| 13 |
results: []
|
| 14 |
---
|
| 15 |
|
| 16 |
+
drone-DinoVdeau-produttoria_binary-binary is a fine-tuned version of [drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze](https://huggingface.co/drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze). It achieves the following results on the test set:
|
|
|
|
| 17 |
|
|
|
|
| 18 |
|
|
|
|
|
|
|
| 19 |
- Loss: 0.2854
|
| 20 |
- F1 Micro: 0.8468
|
| 21 |
- F1 Macro: 0.6351
|
| 22 |
- Accuracy: 0.2786
|
|
|
|
| 23 |
|
| 24 |
+
| Class | F1 per class |
|
| 25 |
+
|----------|-------|
|
| 26 |
+
| Acropore_branched | 0.8084 |
|
| 27 |
+
| Acropore_digitised | 0.5125 |
|
| 28 |
+
| Acropore_tabular | 0.3951 |
|
| 29 |
+
| Algae | 0.9562 |
|
| 30 |
+
| Dead_coral | 0.7470 |
|
| 31 |
+
| Fish | 0.6639 |
|
| 32 |
+
| Millepore | 0.3021 |
|
| 33 |
+
| No_acropore_encrusting | 0.5923 |
|
| 34 |
+
| No_acropore_massive | 0.7651 |
|
| 35 |
+
| No_acropore_sub_massive | 0.6345 |
|
| 36 |
+
| Rock | 0.9536 |
|
| 37 |
+
| Rubble | 0.9042 |
|
| 38 |
+
| Sand | 0.9008 |
|
| 39 |
+
|
| 40 |
|
| 41 |
+
---
|
| 42 |
|
| 43 |
+
# Model description
|
| 44 |
+
drone-DinoVdeau-produttoria_binary-binary is a model built on top of drone-DinoVdeau-produttoria_binary-binary-large-2024_11_03-batch-size64_freeze model for underwater multilabel image classification.The classification head is a combination of linear, ReLU, batch normalization, and dropout layers.
|
| 45 |
|
| 46 |
+
The source code for training the model can be found in this [Git repository](https://github.com/SeatizenDOI/DinoVdeau).
|
| 47 |
|
| 48 |
+
- **Developed by:** [lombardata](https://huggingface.co/lombardata), credits to [César Leblanc](https://huggingface.co/CesarLeblanc) and [Victor Illien](https://huggingface.co/groderg)
|
| 49 |
+
|
| 50 |
+
---
|
| 51 |
|
| 52 |
+
# Intended uses & limitations
|
| 53 |
+
You can use the raw model for classify diverse marine species, encompassing coral morphotypes classes taken from the Global Coral Reef Monitoring Network (GCRMN), habitats classes and seagrass species.
|
| 54 |
|
| 55 |
+
---
|
| 56 |
+
|
| 57 |
+
# Training and evaluation data
|
| 58 |
+
Details on the number of images for each class are given in the following table:
|
| 59 |
+
| Class | train | test | val | Total |
|
| 60 |
+
|:------------------------|--------:|-------:|------:|--------:|
|
| 61 |
+
| Acropore_branched | 1483 | 522 | 529 | 2534 |
|
| 62 |
+
| Acropore_digitised | 1085 | 371 | 362 | 1818 |
|
| 63 |
+
| Acropore_tabular | 486 | 176 | 178 | 840 |
|
| 64 |
+
| Algae | 10340 | 3441 | 3461 | 17242 |
|
| 65 |
+
| Dead_coral | 3710 | 1252 | 1267 | 6229 |
|
| 66 |
+
| Fish | 1462 | 517 | 515 | 2494 |
|
| 67 |
+
| Millepore | 746 | 282 | 273 | 1301 |
|
| 68 |
+
| No_acropore_encrusting | 1993 | 751 | 728 | 3472 |
|
| 69 |
+
| No_acropore_massive | 4450 | 1581 | 1649 | 7680 |
|
| 70 |
+
| No_acropore_sub_massive | 3034 | 1102 | 1113 | 5249 |
|
| 71 |
+
| Rock | 10225 | 3429 | 3445 | 17099 |
|
| 72 |
+
| Rubble | 9353 | 3100 | 3105 | 15558 |
|
| 73 |
+
| Sand | 9271 | 3101 | 3132 | 15504 |
|
| 74 |
+
|
| 75 |
+
---
|
| 76 |
|
| 77 |
+
# Training procedure
|
| 78 |
+
|
| 79 |
+
## Training hyperparameters
|
| 80 |
|
| 81 |
The following hyperparameters were used during training:
|
| 82 |
+
|
| 83 |
+
- **Number of Epochs**: 88.0
|
| 84 |
+
- **Learning Rate**: 0.001
|
| 85 |
+
- **Train Batch Size**: 64
|
| 86 |
+
- **Eval Batch Size**: 64
|
| 87 |
+
- **Optimizer**: Adam
|
| 88 |
+
- **LR Scheduler Type**: ReduceLROnPlateau with a patience of 5 epochs and a factor of 0.1
|
| 89 |
+
- **Freeze Encoder**: Yes
|
| 90 |
+
- **Data Augmentation**: Yes
|
| 91 |
+
|
| 92 |
+
|
| 93 |
+
## Data Augmentation
|
| 94 |
+
Data were augmented using the following transformations :
|
| 95 |
+
|
| 96 |
+
Train Transforms
|
| 97 |
+
- **PreProcess**: No additional parameters
|
| 98 |
+
- **Resize**: probability=1.00
|
| 99 |
+
- **RandomHorizontalFlip**: probability=0.25
|
| 100 |
+
- **RandomVerticalFlip**: probability=0.25
|
| 101 |
+
- **ColorJiggle**: probability=0.25
|
| 102 |
+
- **RandomPerspective**: probability=0.25
|
| 103 |
+
- **Normalize**: probability=1.00
|
| 104 |
+
|
| 105 |
+
Val Transforms
|
| 106 |
+
- **PreProcess**: No additional parameters
|
| 107 |
+
- **Resize**: probability=1.00
|
| 108 |
+
- **Normalize**: probability=1.00
|
| 109 |
+
|
| 110 |
+
|
| 111 |
+
|
| 112 |
+
## Training results
|
| 113 |
+
Epoch | Validation Loss | Accuracy | F1 Macro | F1 Micro | Learning Rate
|
| 114 |
+
--- | --- | --- | --- | --- | ---
|
| 115 |
+
1 | 0.3235681354999542 | 0.2630072840790843 | 0.8262109753225342 | 0.5774239185038708 | 0.001
|
| 116 |
+
2 | 0.3146470785140991 | 0.24115504682622269 | 0.8378565084377776 | 0.6199165901601139 | 0.001
|
| 117 |
+
3 | 0.3090434670448303 | 0.2554630593132154 | 0.8398465111582348 | 0.6043570009634397 | 0.001
|
| 118 |
+
4 | 0.30735355615615845 | 0.25624349635796045 | 0.8348980169243037 | 0.600278483167516 | 0.001
|
| 119 |
+
5 | 0.30385810136795044 | 0.2515608740894901 | 0.8405948994360434 | 0.6247746971203368 | 0.001
|
| 120 |
+
6 | 0.3059956729412079 | 0.2596253902185224 | 0.841987466427932 | 0.6225111439021958 | 0.001
|
| 121 |
+
7 | 0.3013758361339569 | 0.28199791883454733 | 0.8387498056289846 | 0.5954695621655504 | 0.001
|
| 122 |
+
8 | 0.30131709575653076 | 0.2702913631633715 | 0.8390550208451284 | 0.5974832028652961 | 0.001
|
| 123 |
+
9 | 0.30098479986190796 | 0.28407908428720086 | 0.8406665130922214 | 0.5974259992816957 | 0.001
|
| 124 |
+
10 | 0.30072343349456787 | 0.27107180020811655 | 0.8376187886791475 | 0.5937940362628795 | 0.001
|
| 125 |
+
11 | 0.3035621643066406 | 0.277315296566077 | 0.8348592565387339 | 0.5761905737205768 | 0.001
|
| 126 |
+
12 | 0.3012838363647461 | 0.26742976066597296 | 0.838466245156027 | 0.6114755503631268 | 0.001
|
| 127 |
+
13 | 0.29778778553009033 | 0.2648283038501561 | 0.8421213122252433 | 0.6145726431106396 | 0.001
|
| 128 |
+
14 | 0.29774588346481323 | 0.27341311134235174 | 0.8399742101869762 | 0.605884177295118 | 0.001
|
| 129 |
+
15 | 0.29809942841529846 | 0.2666493236212279 | 0.8433503513117323 | 0.6074624445346274 | 0.001
|
| 130 |
+
16 | 0.29744812846183777 | 0.27471383975026015 | 0.8394100355835181 | 0.5932952143692389 | 0.001
|
| 131 |
+
17 | 0.2983638644218445 | 0.2663891779396462 | 0.8437578624264077 | 0.6146867059353278 | 0.001
|
| 132 |
+
18 | 0.3023049235343933 | 0.2762747138397503 | 0.8356339535005088 | 0.5803903225868541 | 0.001
|
| 133 |
+
19 | 0.2984697222709656 | 0.2739334027055151 | 0.8423529411764706 | 0.6158875389283108 | 0.001
|
| 134 |
+
20 | 0.29680272936820984 | 0.28069719042663893 | 0.8411767731317183 | 0.5984147849283556 | 0.001
|
| 135 |
+
21 | 0.30051520466804504 | 0.2702913631633715 | 0.8418969323285377 | 0.6060492619397649 | 0.001
|
| 136 |
+
22 | 0.29818177223205566 | 0.27471383975026015 | 0.8374817746302854 | 0.580353532272699 | 0.001
|
| 137 |
+
23 | 0.29393449425697327 | 0.27809573361082207 | 0.8436262061960386 | 0.615237110287355 | 0.001
|
| 138 |
+
24 | 0.2948347330093384 | 0.27601456815816855 | 0.8453232862164007 | 0.6228721497006335 | 0.001
|
| 139 |
+
25 | 0.29676035046577454 | 0.2736732570239334 | 0.8427456149244652 | 0.610255370235793 | 0.001
|
| 140 |
+
26 | 0.2955995500087738 | 0.2754942767950052 | 0.8420542140997499 | 0.6045462014226007 | 0.001
|
| 141 |
+
27 | 0.29585039615631104 | 0.27653485952133194 | 0.8437684356323902 | 0.6115221375683754 | 0.001
|
| 142 |
+
28 | 0.295540988445282 | 0.26925078043704476 | 0.8446938104986479 | 0.6191186747828321 | 0.001
|
| 143 |
+
29 | 0.3010655343532562 | 0.2663891779396462 | 0.8437664387164651 | 0.6215750043898619 | 0.001
|
| 144 |
+
30 | 0.29214760661125183 | 0.2809573361082206 | 0.8437435686355217 | 0.6025311078598518 | 0.0001
|
| 145 |
+
31 | 0.29040178656578064 | 0.28121748178980227 | 0.8439103638567266 | 0.6071651131848005 | 0.0001
|
| 146 |
+
32 | 0.29034462571144104 | 0.2809573361082206 | 0.8437194965322373 | 0.6111569473926136 | 0.0001
|
| 147 |
+
33 | 0.2888760268688202 | 0.28537981269510926 | 0.8461617038663874 | 0.6202495870793918 | 0.0001
|
| 148 |
+
34 | 0.28964364528656006 | 0.2861602497398543 | 0.8446023671361742 | 0.6150504150317478 | 0.0001
|
| 149 |
+
35 | 0.28874215483665466 | 0.2866805411030177 | 0.8449244728566273 | 0.611180048847438 | 0.0001
|
| 150 |
+
36 | 0.2888963222503662 | 0.28355879292403746 | 0.8447173058645225 | 0.6119874534823754 | 0.0001
|
| 151 |
+
37 | 0.288282573223114 | 0.2866805411030177 | 0.8475834540970686 | 0.6255767175486281 | 0.0001
|
| 152 |
+
38 | 0.29050976037979126 | 0.28251821019771073 | 0.8452536426724028 | 0.6057239934398935 | 0.0001
|
| 153 |
+
39 | 0.28778275847435 | 0.28537981269510926 | 0.8470600182796791 | 0.625366961909805 | 0.0001
|
| 154 |
+
40 | 0.2885717749595642 | 0.2809573361082206 | 0.8468000302716884 | 0.622337777946806 | 0.0001
|
| 155 |
+
41 | 0.28773826360702515 | 0.2843392299687825 | 0.847323400258903 | 0.6260539681026288 | 0.0001
|
| 156 |
+
42 | 0.28776827454566956 | 0.28563995837669093 | 0.8476613005450627 | 0.6199392946357273 | 0.0001
|
| 157 |
+
43 | 0.28717148303985596 | 0.28303850156087407 | 0.8479237095716232 | 0.6287571427217789 | 0.0001
|
| 158 |
+
44 | 0.28678667545318604 | 0.28407908428720086 | 0.8463665693654939 | 0.6189979239207937 | 0.0001
|
| 159 |
+
45 | 0.28698909282684326 | 0.28381893860561913 | 0.8462928555066304 | 0.6235508782461164 | 0.0001
|
| 160 |
+
46 | 0.2868472635746002 | 0.28251821019771073 | 0.8459846547314578 | 0.6151318511304835 | 0.0001
|
| 161 |
+
47 | 0.28715068101882935 | 0.2845993756503642 | 0.8462129359348595 | 0.6211457155619424 | 0.0001
|
| 162 |
+
48 | 0.28661593794822693 | 0.28355879292403746 | 0.8466852933705867 | 0.6231150403485404 | 0.0001
|
| 163 |
+
49 | 0.28633347153663635 | 0.28590010405827265 | 0.8460415439387342 | 0.616055362439494 | 0.0001
|
| 164 |
+
50 | 0.28642749786376953 | 0.2845993756503642 | 0.8482882700250868 | 0.625458075101288 | 0.0001
|
| 165 |
+
51 | 0.2890762686729431 | 0.28485952133194586 | 0.848592785832539 | 0.6278100779578839 | 0.0001
|
| 166 |
+
52 | 0.2855978012084961 | 0.2851196670135276 | 0.8464228285561143 | 0.6255462096645672 | 0.0001
|
| 167 |
+
53 | 0.2872205674648285 | 0.27887617065556713 | 0.8489991514001897 | 0.6457587856102145 | 0.0001
|
| 168 |
+
54 | 0.2855803072452545 | 0.2903225806451613 | 0.8476844874709444 | 0.6243869856844756 | 0.0001
|
| 169 |
+
55 | 0.28568968176841736 | 0.2845993756503642 | 0.8475136716266056 | 0.6339630509281279 | 0.0001
|
| 170 |
+
56 | 0.28617897629737854 | 0.2866805411030177 | 0.8465597622829039 | 0.6241465491773776 | 0.0001
|
| 171 |
+
57 | 0.2870914936065674 | 0.2861602497398543 | 0.845436853426201 | 0.6249269702519318 | 0.0001
|
| 172 |
+
58 | 0.2857914865016937 | 0.28121748178980227 | 0.8491941382702348 | 0.6333866717026029 | 0.0001
|
| 173 |
+
59 | 0.28617140650749207 | 0.2887617065556712 | 0.8468232576049287 | 0.6178461796051926 | 1e-05
|
| 174 |
+
60 | 0.2846605181694031 | 0.28537981269510926 | 0.8485033598045205 | 0.6275748058546806 | 1e-05
|
| 175 |
+
61 | 0.2848633825778961 | 0.28303850156087407 | 0.8479865171982329 | 0.6223888517425455 | 1e-05
|
| 176 |
+
62 | 0.28548601269721985 | 0.2843392299687825 | 0.8469200122586577 | 0.6247632003821695 | 1e-05
|
| 177 |
+
63 | 0.28493326902389526 | 0.2827783558792924 | 0.8488979777323336 | 0.6274806463168713 | 1e-05
|
| 178 |
+
64 | 0.28459736704826355 | 0.28225806451612906 | 0.8475187206498287 | 0.6370787064578803 | 1e-05
|
| 179 |
+
65 | 0.2860054671764374 | 0.2869406867845994 | 0.8467700785794469 | 0.6240984315849201 | 1e-05
|
| 180 |
+
66 | 0.2847185730934143 | 0.28407908428720086 | 0.8481340441736481 | 0.6346693986906206 | 1e-05
|
| 181 |
+
67 | 0.28529325127601624 | 0.28537981269510926 | 0.8487528745798691 | 0.6287121285420982 | 1e-05
|
| 182 |
+
68 | 0.2852926254272461 | 0.2866805411030177 | 0.8480251642525557 | 0.6321379394582358 | 1e-05
|
| 183 |
+
69 | 0.284834623336792 | 0.28355879292403746 | 0.847692190707931 | 0.6397237492354447 | 1e-05
|
| 184 |
+
70 | 0.28527727723121643 | 0.28225806451612906 | 0.8492167101827677 | 0.6381143671040704 | 1e-05
|
| 185 |
+
71 | 0.28507113456726074 | 0.2882414151925078 | 0.8475971370143149 | 0.6325489300082728 | 1.0000000000000002e-06
|
| 186 |
+
72 | 0.28452861309051514 | 0.28485952133194586 | 0.8474255781269963 | 0.6236352127811986 | 1.0000000000000002e-06
|
| 187 |
+
73 | 0.28448227047920227 | 0.28121748178980227 | 0.847641772858811 | 0.6333277250193455 | 1.0000000000000002e-06
|
| 188 |
+
74 | 0.28447526693344116 | 0.2827783558792924 | 0.8465770953294945 | 0.6300187593616763 | 1.0000000000000002e-06
|
| 189 |
+
75 | 0.2851284146308899 | 0.28199791883454733 | 0.8473772748126625 | 0.6235297745568456 | 1.0000000000000002e-06
|
| 190 |
+
76 | 0.2859683036804199 | 0.2879812695109261 | 0.847320835674516 | 0.6186062513830065 | 1.0000000000000002e-06
|
| 191 |
+
77 | 0.2858298718929291 | 0.28563995837669093 | 0.8459046737621472 | 0.6172786558676017 | 1.0000000000000002e-06
|
| 192 |
+
78 | 0.28438833355903625 | 0.2843392299687825 | 0.8480547459130655 | 0.6325947858436887 | 1.0000000000000002e-06
|
| 193 |
+
79 | 0.2870919704437256 | 0.2874609781477627 | 0.8472353346431579 | 0.617917490234713 | 1.0000000000000002e-06
|
| 194 |
+
80 | 0.28482332825660706 | 0.28381893860561913 | 0.8477330616403465 | 0.6286567457369128 | 1.0000000000000002e-06
|
| 195 |
+
81 | 0.2847617268562317 | 0.28537981269510926 | 0.8489678202792957 | 0.6304525529970205 | 1.0000000000000002e-06
|
| 196 |
+
82 | 0.28511229157447815 | 0.28590010405827265 | 0.8480416961845967 | 0.6394217270135759 | 1.0000000000000002e-06
|
| 197 |
+
83 | 0.284644216299057 | 0.28563995837669093 | 0.8488055562622434 | 0.6255055774993536 | 1.0000000000000002e-06
|
| 198 |
+
84 | 0.2857225835323334 | 0.2832986472424558 | 0.848188643119867 | 0.6457553263622914 | 1.0000000000000002e-06
|
| 199 |
+
85 | 0.28550758957862854 | 0.28121748178980227 | 0.848818698673405 | 0.6339586571635658 | 1.0000000000000002e-07
|
| 200 |
+
86 | 0.284895658493042 | 0.28590010405827265 | 0.8479890588592848 | 0.6362631688004041 | 1.0000000000000002e-07
|
| 201 |
+
87 | 0.2845035493373871 | 0.2851196670135276 | 0.8473590201582036 | 0.6327749126527296 | 1.0000000000000002e-07
|
| 202 |
+
88 | 0.28541097044944763 | 0.28121748178980227 | 0.8477551536613127 | 0.6370893160624239 | 1.0000000000000002e-07
|
| 203 |
+
|
| 204 |
+
|
| 205 |
+
---
|
| 206 |
+
|
| 207 |
+
# Framework Versions
|
| 208 |
+
|
| 209 |
+
- **Transformers**: 4.41.0
|
| 210 |
+
- **Pytorch**: 2.5.0+cu124
|
| 211 |
+
- **Datasets**: 3.0.2
|
| 212 |
+
- **Tokenizers**: 0.19.1
|
| 213 |
+
|