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visual-emotion-recognition

Image Classification
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vit
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End of training

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README.md CHANGED
@@ -25,16 +25,16 @@ model-index:
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  metrics:
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  - name: Accuracy
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  type: accuracy
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- value: 0.6171875
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  - name: Precision
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  type: precision
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- value: 0.6123019520308124
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  - name: Recall
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  type: recall
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- value: 0.6171875
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  - name: F1
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  type: f1
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- value: 0.6099565615619817
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  ---
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  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
@@ -44,11 +44,11 @@ should probably proofread and complete it, then remove this comment. -->
44
 
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  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
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  It achieves the following results on the evaluation set:
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- - Loss: 1.2563
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- - Accuracy: 0.6172
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- - Precision: 0.6123
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- - Recall: 0.6172
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- - F1: 0.6100
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  ## Model description
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@@ -68,11 +68,11 @@ More information needed
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  The following hyperparameters were used during training:
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  - learning_rate: 1e-05
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- - train_batch_size: 32
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- - eval_batch_size: 32
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  - seed: 42
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  - gradient_accumulation_steps: 3
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- - total_train_batch_size: 96
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
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  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
@@ -83,100 +83,104 @@ The following hyperparameters were used during training:
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  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
85
  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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- | 2.0811 | 0.94 | 5 | 2.0911 | 0.0859 | 0.0534 | 0.0859 | 0.0658 |
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- | 2.0668 | 1.88 | 10 | 2.0830 | 0.1016 | 0.0654 | 0.1016 | 0.0758 |
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- | 2.057 | 3.0 | 16 | 2.0733 | 0.1328 | 0.1119 | 0.1328 | 0.1066 |
89
- | 2.0445 | 3.94 | 21 | 2.0643 | 0.1328 | 0.0965 | 0.1328 | 0.1000 |
90
- | 2.0198 | 4.88 | 26 | 2.0537 | 0.1797 | 0.1911 | 0.1797 | 0.1604 |
91
- | 2.008 | 6.0 | 32 | 2.0387 | 0.1797 | 0.1669 | 0.1797 | 0.1513 |
92
- | 1.9937 | 6.94 | 37 | 2.0241 | 0.1875 | 0.1773 | 0.1875 | 0.1595 |
93
- | 1.9711 | 7.88 | 42 | 2.0078 | 0.2031 | 0.1939 | 0.2031 | 0.1737 |
94
- | 1.9468 | 9.0 | 48 | 1.9872 | 0.2578 | 0.2619 | 0.2578 | 0.2231 |
95
- | 1.9184 | 9.94 | 53 | 1.9663 | 0.2969 | 0.3203 | 0.2969 | 0.2609 |
96
- | 1.9042 | 10.88 | 58 | 1.9428 | 0.3047 | 0.3410 | 0.3047 | 0.2711 |
97
- | 1.8673 | 12.0 | 64 | 1.9127 | 0.3047 | 0.3731 | 0.3047 | 0.2730 |
98
- | 1.8449 | 12.94 | 69 | 1.8858 | 0.3203 | 0.4648 | 0.3203 | 0.2835 |
99
- | 1.8019 | 13.88 | 74 | 1.8572 | 0.3203 | 0.4856 | 0.3203 | 0.2924 |
100
- | 1.7438 | 15.0 | 80 | 1.8182 | 0.3203 | 0.4643 | 0.3203 | 0.3016 |
101
- | 1.7037 | 15.94 | 85 | 1.7909 | 0.3438 | 0.4862 | 0.3438 | 0.3339 |
102
- | 1.6787 | 16.88 | 90 | 1.7651 | 0.3438 | 0.4510 | 0.3438 | 0.3339 |
103
- | 1.6514 | 18.0 | 96 | 1.7360 | 0.3672 | 0.4630 | 0.3672 | 0.3641 |
104
- | 1.6322 | 18.94 | 101 | 1.7153 | 0.3828 | 0.4710 | 0.3828 | 0.3783 |
105
- | 1.5861 | 19.88 | 106 | 1.6980 | 0.4062 | 0.5040 | 0.4062 | 0.3963 |
106
- | 1.5871 | 21.0 | 112 | 1.6797 | 0.4219 | 0.4768 | 0.4219 | 0.4134 |
107
- | 1.5709 | 21.94 | 117 | 1.6635 | 0.4062 | 0.4665 | 0.4062 | 0.4038 |
108
- | 1.5296 | 22.88 | 122 | 1.6470 | 0.4297 | 0.4772 | 0.4297 | 0.4213 |
109
- | 1.5168 | 24.0 | 128 | 1.6318 | 0.4297 | 0.4712 | 0.4297 | 0.4234 |
110
- | 1.5105 | 24.94 | 133 | 1.6174 | 0.4609 | 0.4858 | 0.4609 | 0.4478 |
111
- | 1.485 | 25.88 | 138 | 1.6024 | 0.4766 | 0.5290 | 0.4766 | 0.4717 |
112
- | 1.4565 | 27.0 | 144 | 1.5929 | 0.4609 | 0.4800 | 0.4609 | 0.4517 |
113
- | 1.4273 | 27.94 | 149 | 1.5803 | 0.4688 | 0.4800 | 0.4688 | 0.4581 |
114
- | 1.4375 | 28.88 | 154 | 1.5650 | 0.5234 | 0.5527 | 0.5234 | 0.5134 |
115
- | 1.3806 | 30.0 | 160 | 1.5563 | 0.4688 | 0.5052 | 0.4688 | 0.4651 |
116
- | 1.3686 | 30.94 | 165 | 1.5443 | 0.5 | 0.5381 | 0.5 | 0.4969 |
117
- | 1.3636 | 31.88 | 170 | 1.5273 | 0.5234 | 0.5459 | 0.5234 | 0.5152 |
118
- | 1.3295 | 33.0 | 176 | 1.5175 | 0.5234 | 0.5444 | 0.5234 | 0.5160 |
119
- | 1.3426 | 33.94 | 181 | 1.5115 | 0.5078 | 0.5179 | 0.5078 | 0.5030 |
120
- | 1.2963 | 34.88 | 186 | 1.4918 | 0.5234 | 0.5399 | 0.5234 | 0.5133 |
121
- | 1.2917 | 36.0 | 192 | 1.4832 | 0.5391 | 0.5436 | 0.5391 | 0.5294 |
122
- | 1.2733 | 36.94 | 197 | 1.4718 | 0.5547 | 0.5730 | 0.5547 | 0.5475 |
123
- | 1.2398 | 37.88 | 202 | 1.4556 | 0.5703 | 0.5996 | 0.5703 | 0.5642 |
124
- | 1.2472 | 39.0 | 208 | 1.4575 | 0.5625 | 0.5820 | 0.5625 | 0.5600 |
125
- | 1.2286 | 39.94 | 213 | 1.4426 | 0.5781 | 0.6024 | 0.5781 | 0.5728 |
126
- | 1.1882 | 40.88 | 218 | 1.4277 | 0.5625 | 0.5787 | 0.5625 | 0.5532 |
127
- | 1.1833 | 42.0 | 224 | 1.4209 | 0.5625 | 0.5857 | 0.5625 | 0.5579 |
128
- | 1.1592 | 42.94 | 229 | 1.4171 | 0.5781 | 0.6089 | 0.5781 | 0.5766 |
129
- | 1.1386 | 43.88 | 234 | 1.4046 | 0.5859 | 0.6053 | 0.5859 | 0.5790 |
130
- | 1.118 | 45.0 | 240 | 1.3985 | 0.5547 | 0.5772 | 0.5547 | 0.5507 |
131
- | 1.1151 | 45.94 | 245 | 1.3996 | 0.5703 | 0.6026 | 0.5703 | 0.5701 |
132
- | 1.0848 | 46.88 | 250 | 1.3782 | 0.5703 | 0.5885 | 0.5703 | 0.5667 |
133
- | 1.0729 | 48.0 | 256 | 1.3891 | 0.5703 | 0.5809 | 0.5703 | 0.5641 |
134
- | 1.0702 | 48.94 | 261 | 1.3749 | 0.5625 | 0.5861 | 0.5625 | 0.5586 |
135
- | 1.0408 | 49.88 | 266 | 1.3725 | 0.5625 | 0.5732 | 0.5625 | 0.5561 |
136
- | 1.0274 | 51.0 | 272 | 1.3644 | 0.5547 | 0.5572 | 0.5547 | 0.5461 |
137
- | 1.0321 | 51.94 | 277 | 1.3651 | 0.5625 | 0.5841 | 0.5625 | 0.5587 |
138
- | 0.9872 | 52.88 | 282 | 1.3617 | 0.5547 | 0.5670 | 0.5547 | 0.5480 |
139
- | 0.9991 | 54.0 | 288 | 1.3496 | 0.5859 | 0.5902 | 0.5859 | 0.5774 |
140
- | 0.9891 | 54.94 | 293 | 1.3619 | 0.5781 | 0.5990 | 0.5781 | 0.5770 |
141
- | 0.9654 | 55.88 | 298 | 1.3322 | 0.5625 | 0.5830 | 0.5625 | 0.5609 |
142
- | 0.9489 | 57.0 | 304 | 1.3338 | 0.5781 | 0.5968 | 0.5781 | 0.5762 |
143
- | 0.9346 | 57.94 | 309 | 1.3332 | 0.5781 | 0.6057 | 0.5781 | 0.5796 |
144
- | 0.8965 | 58.88 | 314 | 1.3239 | 0.5781 | 0.6057 | 0.5781 | 0.5796 |
145
- | 0.8809 | 60.0 | 320 | 1.3269 | 0.5938 | 0.6005 | 0.5938 | 0.5885 |
146
- | 0.8928 | 60.94 | 325 | 1.3168 | 0.5703 | 0.5873 | 0.5703 | 0.5687 |
147
- | 0.8662 | 61.88 | 330 | 1.3241 | 0.5625 | 0.5889 | 0.5625 | 0.5641 |
148
- | 0.8496 | 63.0 | 336 | 1.3062 | 0.5703 | 0.5832 | 0.5703 | 0.5648 |
149
- | 0.8485 | 63.94 | 341 | 1.2968 | 0.5859 | 0.5776 | 0.5859 | 0.5734 |
150
- | 0.8425 | 64.88 | 346 | 1.3093 | 0.5781 | 0.5775 | 0.5781 | 0.5683 |
151
- | 0.8175 | 66.0 | 352 | 1.2888 | 0.5859 | 0.6029 | 0.5859 | 0.5851 |
152
- | 0.7942 | 66.94 | 357 | 1.3084 | 0.5781 | 0.5764 | 0.5781 | 0.5674 |
153
- | 0.7865 | 67.88 | 362 | 1.3040 | 0.5938 | 0.6029 | 0.5938 | 0.5897 |
154
- | 0.7376 | 69.0 | 368 | 1.2982 | 0.5781 | 0.5968 | 0.5781 | 0.5773 |
155
- | 0.7838 | 69.94 | 373 | 1.2960 | 0.5703 | 0.5851 | 0.5703 | 0.5676 |
156
- | 0.7779 | 70.88 | 378 | 1.2876 | 0.6016 | 0.5996 | 0.6016 | 0.5925 |
157
- | 0.7259 | 72.0 | 384 | 1.2898 | 0.5781 | 0.5805 | 0.5781 | 0.5716 |
158
- | 0.7242 | 72.94 | 389 | 1.2891 | 0.5859 | 0.6073 | 0.5859 | 0.5869 |
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- | 0.7185 | 73.88 | 394 | 1.2800 | 0.6094 | 0.6131 | 0.6094 | 0.6048 |
160
- | 0.7366 | 75.0 | 400 | 1.2762 | 0.5781 | 0.5807 | 0.5781 | 0.5721 |
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- | 0.7194 | 75.94 | 405 | 1.2847 | 0.5938 | 0.6019 | 0.5938 | 0.5898 |
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- | 0.6699 | 76.88 | 410 | 1.2563 | 0.6172 | 0.6123 | 0.6172 | 0.6100 |
163
- | 0.6958 | 78.0 | 416 | 1.2937 | 0.5703 | 0.5764 | 0.5703 | 0.5609 |
164
- | 0.6673 | 78.94 | 421 | 1.2626 | 0.6094 | 0.6008 | 0.6094 | 0.5998 |
165
- | 0.6443 | 79.88 | 426 | 1.2561 | 0.5781 | 0.5820 | 0.5781 | 0.5734 |
166
- | 0.642 | 81.0 | 432 | 1.2654 | 0.5938 | 0.6009 | 0.5938 | 0.5910 |
167
- | 0.6536 | 81.94 | 437 | 1.2604 | 0.5781 | 0.5938 | 0.5781 | 0.5773 |
168
- | 0.5973 | 82.88 | 442 | 1.2783 | 0.5938 | 0.6081 | 0.5938 | 0.5927 |
169
- | 0.6074 | 84.0 | 448 | 1.2709 | 0.5938 | 0.6041 | 0.5938 | 0.5865 |
170
- | 0.6419 | 84.94 | 453 | 1.2820 | 0.5781 | 0.5815 | 0.5781 | 0.5680 |
171
- | 0.611 | 85.88 | 458 | 1.2447 | 0.5625 | 0.5678 | 0.5625 | 0.5601 |
172
- | 0.606 | 87.0 | 464 | 1.3020 | 0.5781 | 0.5889 | 0.5781 | 0.5711 |
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- | 0.5996 | 87.94 | 469 | 1.2690 | 0.5859 | 0.6016 | 0.5859 | 0.5862 |
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- | 0.5962 | 88.88 | 474 | 1.2713 | 0.5781 | 0.5787 | 0.5781 | 0.5699 |
175
- | 0.5423 | 90.0 | 480 | 1.2856 | 0.5703 | 0.5803 | 0.5703 | 0.5688 |
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- | 0.5693 | 90.94 | 485 | 1.2512 | 0.5703 | 0.5886 | 0.5703 | 0.5724 |
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- | 0.5426 | 91.88 | 490 | 1.2654 | 0.5859 | 0.5881 | 0.5859 | 0.5808 |
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- | 0.5676 | 93.0 | 496 | 1.2829 | 0.5703 | 0.5818 | 0.5703 | 0.5702 |
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- | 0.5275 | 93.75 | 500 | 1.2630 | 0.5391 | 0.5541 | 0.5391 | 0.5428 |
 
 
 
 
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  ### Framework versions
 
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  metrics:
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  - name: Accuracy
27
  type: accuracy
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+ value: 0.6375
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  - name: Precision
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  type: precision
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+ value: 0.6498416164333246
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  - name: Recall
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  type: recall
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+ value: 0.6375
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  - name: F1
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  type: f1
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+ value: 0.6340720916258936
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  ---
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40
  <!-- This model card has been generated automatically according to the information the Trainer had access to. You
 
44
 
45
  This model is a fine-tuned version of [google/vit-base-patch16-224-in21k](https://huggingface.co/google/vit-base-patch16-224-in21k) on the imagefolder dataset.
46
  It achieves the following results on the evaluation set:
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+ - Loss: 1.1334
48
+ - Accuracy: 0.6375
49
+ - Precision: 0.6498
50
+ - Recall: 0.6375
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+ - F1: 0.6341
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53
  ## Model description
54
 
 
68
 
69
  The following hyperparameters were used during training:
70
  - learning_rate: 1e-05
71
+ - train_batch_size: 16
72
+ - eval_batch_size: 16
73
  - seed: 42
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  - gradient_accumulation_steps: 3
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+ - total_train_batch_size: 48
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  - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
77
  - lr_scheduler_type: linear
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  - lr_scheduler_warmup_ratio: 0.1
 
83
 
84
  | Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
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  |:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|:------:|
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+ | 2.0671 | 0.97 | 13 | 2.0660 | 0.125 | 0.2709 | 0.125 | 0.1135 |
87
+ | 2.0576 | 1.95 | 26 | 2.0563 | 0.1562 | 0.2932 | 0.1562 | 0.1402 |
88
+ | 2.044 | 3.0 | 40 | 2.0439 | 0.1875 | 0.2554 | 0.1875 | 0.1827 |
89
+ | 2.0209 | 3.98 | 53 | 2.0309 | 0.2062 | 0.2405 | 0.2062 | 0.1961 |
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+ | 1.9938 | 4.95 | 66 | 2.0176 | 0.2188 | 0.2410 | 0.2188 | 0.2062 |
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+ | 1.9894 | 6.0 | 80 | 1.9960 | 0.2625 | 0.2700 | 0.2625 | 0.2438 |
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+ | 1.9667 | 6.97 | 93 | 1.9743 | 0.3125 | 0.3089 | 0.3125 | 0.2901 |
93
+ | 1.9158 | 7.95 | 106 | 1.9421 | 0.3063 | 0.2557 | 0.3063 | 0.2687 |
94
+ | 1.8834 | 9.0 | 120 | 1.9042 | 0.3375 | 0.4019 | 0.3375 | 0.2888 |
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+ | 1.8461 | 9.97 | 133 | 1.8521 | 0.3625 | 0.4132 | 0.3625 | 0.3021 |
96
+ | 1.7917 | 10.95 | 146 | 1.8023 | 0.3688 | 0.4144 | 0.3688 | 0.3056 |
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+ | 1.7685 | 12.0 | 160 | 1.7552 | 0.375 | 0.4062 | 0.375 | 0.2978 |
98
+ | 1.7072 | 12.97 | 173 | 1.7071 | 0.3875 | 0.4266 | 0.3875 | 0.3164 |
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+ | 1.6926 | 13.95 | 186 | 1.6742 | 0.375 | 0.4056 | 0.375 | 0.2996 |
100
+ | 1.6084 | 15.0 | 200 | 1.6476 | 0.3937 | 0.4411 | 0.3937 | 0.3358 |
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+ | 1.6264 | 15.97 | 213 | 1.6231 | 0.3812 | 0.4357 | 0.3812 | 0.3311 |
102
+ | 1.5531 | 16.95 | 226 | 1.6019 | 0.4125 | 0.4676 | 0.4125 | 0.3626 |
103
+ | 1.5804 | 18.0 | 240 | 1.5773 | 0.3937 | 0.4442 | 0.3937 | 0.3428 |
104
+ | 1.54 | 18.98 | 253 | 1.5606 | 0.4 | 0.4565 | 0.4 | 0.3527 |
105
+ | 1.5461 | 19.95 | 266 | 1.5464 | 0.4437 | 0.5084 | 0.4437 | 0.4028 |
106
+ | 1.4841 | 21.0 | 280 | 1.5323 | 0.4313 | 0.4950 | 0.4313 | 0.3881 |
107
+ | 1.4765 | 21.98 | 293 | 1.5121 | 0.4313 | 0.4884 | 0.4313 | 0.3822 |
108
+ | 1.4838 | 22.95 | 306 | 1.4978 | 0.4375 | 0.5138 | 0.4375 | 0.4012 |
109
+ | 1.4487 | 24.0 | 320 | 1.4791 | 0.4437 | 0.5059 | 0.4437 | 0.4001 |
110
+ | 1.4272 | 24.98 | 333 | 1.4617 | 0.4562 | 0.5304 | 0.4562 | 0.4180 |
111
+ | 1.3886 | 25.95 | 346 | 1.4488 | 0.4625 | 0.5418 | 0.4625 | 0.4303 |
112
+ | 1.4529 | 27.0 | 360 | 1.4436 | 0.45 | 0.5147 | 0.45 | 0.4035 |
113
+ | 1.3894 | 27.98 | 373 | 1.4267 | 0.4688 | 0.5488 | 0.4688 | 0.4355 |
114
+ | 1.3848 | 28.95 | 386 | 1.4153 | 0.4625 | 0.5337 | 0.4625 | 0.4264 |
115
+ | 1.3561 | 30.0 | 400 | 1.3993 | 0.4875 | 0.5521 | 0.4875 | 0.4554 |
116
+ | 1.3184 | 30.98 | 413 | 1.3852 | 0.4813 | 0.5526 | 0.4813 | 0.4470 |
117
+ | 1.282 | 31.95 | 426 | 1.3703 | 0.4813 | 0.5480 | 0.4813 | 0.4449 |
118
+ | 1.2988 | 33.0 | 440 | 1.3674 | 0.4688 | 0.5541 | 0.4688 | 0.4395 |
119
+ | 1.2507 | 33.98 | 453 | 1.3594 | 0.4688 | 0.5347 | 0.4688 | 0.4307 |
120
+ | 1.2446 | 34.95 | 466 | 1.3519 | 0.4813 | 0.5616 | 0.4813 | 0.4514 |
121
+ | 1.2877 | 36.0 | 480 | 1.3547 | 0.4875 | 0.5599 | 0.4875 | 0.4605 |
122
+ | 1.2237 | 36.98 | 493 | 1.3342 | 0.5 | 0.5744 | 0.5 | 0.4654 |
123
+ | 1.2416 | 37.95 | 506 | 1.3214 | 0.4813 | 0.5693 | 0.4813 | 0.4551 |
124
+ | 1.1786 | 39.0 | 520 | 1.3122 | 0.4875 | 0.5674 | 0.4875 | 0.4586 |
125
+ | 1.193 | 39.98 | 533 | 1.2989 | 0.5 | 0.5755 | 0.5 | 0.4774 |
126
+ | 1.148 | 40.95 | 546 | 1.2962 | 0.5125 | 0.5811 | 0.5125 | 0.4755 |
127
+ | 1.1904 | 42.0 | 560 | 1.2860 | 0.5188 | 0.5863 | 0.5188 | 0.4928 |
128
+ | 1.1311 | 42.98 | 573 | 1.2893 | 0.5312 | 0.5936 | 0.5312 | 0.5117 |
129
+ | 1.1396 | 43.95 | 586 | 1.2860 | 0.4938 | 0.5633 | 0.4938 | 0.4698 |
130
+ | 1.1235 | 45.0 | 600 | 1.2802 | 0.5 | 0.5725 | 0.5 | 0.4758 |
131
+ | 1.1638 | 45.98 | 613 | 1.2596 | 0.525 | 0.5909 | 0.525 | 0.5058 |
132
+ | 1.0777 | 46.95 | 626 | 1.2668 | 0.5188 | 0.5796 | 0.5188 | 0.4861 |
133
+ | 1.1136 | 48.0 | 640 | 1.2520 | 0.55 | 0.6100 | 0.55 | 0.5291 |
134
+ | 1.047 | 48.98 | 653 | 1.2437 | 0.5375 | 0.5963 | 0.5375 | 0.5279 |
135
+ | 1.1101 | 49.95 | 666 | 1.2527 | 0.55 | 0.6195 | 0.55 | 0.5279 |
136
+ | 1.0412 | 51.0 | 680 | 1.2455 | 0.525 | 0.5927 | 0.525 | 0.5156 |
137
+ | 1.041 | 51.98 | 693 | 1.2245 | 0.55 | 0.6073 | 0.55 | 0.5353 |
138
+ | 0.9906 | 52.95 | 706 | 1.2307 | 0.575 | 0.6420 | 0.575 | 0.5600 |
139
+ | 0.9863 | 54.0 | 720 | 1.2307 | 0.5563 | 0.6150 | 0.5563 | 0.5362 |
140
+ | 0.943 | 54.98 | 733 | 1.2270 | 0.55 | 0.6152 | 0.55 | 0.5302 |
141
+ | 0.9557 | 55.95 | 746 | 1.2063 | 0.5312 | 0.5964 | 0.5312 | 0.5239 |
142
+ | 0.9518 | 57.0 | 760 | 1.2122 | 0.55 | 0.6232 | 0.55 | 0.5433 |
143
+ | 0.9545 | 57.98 | 773 | 1.1955 | 0.575 | 0.6144 | 0.575 | 0.5563 |
144
+ | 0.9195 | 58.95 | 786 | 1.2139 | 0.5563 | 0.6052 | 0.5563 | 0.5459 |
145
+ | 0.9267 | 60.0 | 800 | 1.1907 | 0.5687 | 0.6052 | 0.5687 | 0.5595 |
146
+ | 0.9384 | 60.98 | 813 | 1.1899 | 0.575 | 0.6449 | 0.575 | 0.5650 |
147
+ | 0.8727 | 61.95 | 826 | 1.1854 | 0.5813 | 0.6312 | 0.5813 | 0.5651 |
148
+ | 0.8541 | 63.0 | 840 | 1.1957 | 0.575 | 0.6407 | 0.575 | 0.5632 |
149
+ | 0.8899 | 63.98 | 853 | 1.1604 | 0.575 | 0.6196 | 0.575 | 0.5694 |
150
+ | 0.9036 | 64.95 | 866 | 1.1859 | 0.5563 | 0.6310 | 0.5563 | 0.5306 |
151
+ | 0.8177 | 66.0 | 880 | 1.1498 | 0.6125 | 0.6316 | 0.6125 | 0.6116 |
152
+ | 0.7854 | 66.97 | 893 | 1.1842 | 0.5687 | 0.6142 | 0.5687 | 0.5582 |
153
+ | 0.8054 | 67.95 | 906 | 1.1695 | 0.5938 | 0.6275 | 0.5938 | 0.5830 |
154
+ | 0.8582 | 69.0 | 920 | 1.1882 | 0.5687 | 0.6057 | 0.5687 | 0.5495 |
155
+ | 0.7603 | 69.97 | 933 | 1.2067 | 0.55 | 0.6025 | 0.55 | 0.5348 |
156
+ | 0.763 | 70.95 | 946 | 1.1690 | 0.5625 | 0.6036 | 0.5625 | 0.5439 |
157
+ | 0.8261 | 72.0 | 960 | 1.1616 | 0.6062 | 0.6306 | 0.6062 | 0.6016 |
158
+ | 0.884 | 72.97 | 973 | 1.1952 | 0.5625 | 0.6082 | 0.5625 | 0.5436 |
159
+ | 0.7843 | 73.95 | 986 | 1.1583 | 0.5687 | 0.5953 | 0.5687 | 0.5633 |
160
+ | 0.801 | 75.0 | 1000 | 1.1547 | 0.575 | 0.6013 | 0.575 | 0.5745 |
161
+ | 0.7454 | 75.97 | 1013 | 1.1372 | 0.5875 | 0.6193 | 0.5875 | 0.5761 |
162
+ | 0.7325 | 76.95 | 1026 | 1.1696 | 0.5938 | 0.6351 | 0.5938 | 0.5919 |
163
+ | 0.7931 | 78.0 | 1040 | 1.1511 | 0.6062 | 0.6342 | 0.6062 | 0.6053 |
164
+ | 0.7487 | 78.97 | 1053 | 1.1655 | 0.5625 | 0.5898 | 0.5625 | 0.5496 |
165
+ | 0.7262 | 79.95 | 1066 | 1.1394 | 0.6125 | 0.6295 | 0.6125 | 0.6048 |
166
+ | 0.7669 | 81.0 | 1080 | 1.1748 | 0.575 | 0.5966 | 0.575 | 0.5697 |
167
+ | 0.7028 | 81.97 | 1093 | 1.1418 | 0.5875 | 0.6178 | 0.5875 | 0.5885 |
168
+ | 0.7749 | 82.95 | 1106 | 1.1736 | 0.55 | 0.5446 | 0.55 | 0.5255 |
169
+ | 0.7233 | 84.0 | 1120 | 1.1645 | 0.5813 | 0.5973 | 0.5813 | 0.5699 |
170
+ | 0.5915 | 84.97 | 1133 | 1.1376 | 0.5875 | 0.6167 | 0.5875 | 0.5867 |
171
+ | 0.6985 | 85.95 | 1146 | 1.1665 | 0.5687 | 0.5868 | 0.5687 | 0.5533 |
172
+ | 0.6572 | 87.0 | 1160 | 1.1341 | 0.6 | 0.6245 | 0.6 | 0.5963 |
173
+ | 0.6317 | 87.97 | 1173 | 1.1327 | 0.6125 | 0.6288 | 0.6125 | 0.6026 |
174
+ | 0.6546 | 88.95 | 1186 | 1.1668 | 0.5687 | 0.5797 | 0.5687 | 0.5528 |
175
+ | 0.5801 | 90.0 | 1200 | 1.1521 | 0.5875 | 0.6161 | 0.5875 | 0.5818 |
176
+ | 0.6958 | 90.97 | 1213 | 1.1401 | 0.5875 | 0.6083 | 0.5875 | 0.5774 |
177
+ | 0.5856 | 91.95 | 1226 | 1.1379 | 0.5875 | 0.5888 | 0.5875 | 0.5760 |
178
+ | 0.6281 | 93.0 | 1240 | 1.1379 | 0.6125 | 0.6429 | 0.6125 | 0.6123 |
179
+ | 0.6518 | 93.97 | 1253 | 1.1619 | 0.6312 | 0.6547 | 0.6312 | 0.6247 |
180
+ | 0.6055 | 94.95 | 1266 | 1.1700 | 0.575 | 0.5962 | 0.575 | 0.5673 |
181
+ | 0.6181 | 96.0 | 1280 | 1.1550 | 0.5938 | 0.6281 | 0.5938 | 0.5970 |
182
+ | 0.6601 | 96.97 | 1293 | 1.1334 | 0.6375 | 0.6498 | 0.6375 | 0.6341 |
183
+ | 0.6112 | 97.5 | 1300 | 1.1007 | 0.6188 | 0.6341 | 0.6188 | 0.6207 |
184
 
185
 
186
  ### Framework versions
model.safetensors CHANGED
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  size 343242432
 
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  size 343242432
runs/Feb13_02-56-35_0b73b82a108e/events.out.tfevents.1707794948.0b73b82a108e.1967.2 ADDED
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+ version https://git-lfs.github.com/spec/v1
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