Invitrace / I-live-well-foodai

Hiperparámetros de entrenamiento

Los siguientes hiperparámetros se utilizaron durante el entrenamiento:

• learning_rate: 2e-05
• train_batch_size: 8
• eval_batch_size: 8
• seed: 42
• optimizer: Adam con betas=(0.9,0.999) y epsilon=1e-08
• lr_scheduler_type: lineal
• num_epochs: 8
• mixed_precision_training: AMP nativo

## Resultados de entrenamiento 
### Pérdida de entrenamiento 
### Época 
### Paso 
### Pérdida de validación 
### Precisión 

5.0735 
0.0803 
200 
5.0486 
0.0462 

4.947 
0.1605 
400 
4.9254 
0.1136 

4.8134 
0.2408 
600 
4.7931 
0.2101 

4.653 
0.3210 
800 
4.6667 
0.2133 

4.5977 
0.4013 
1000 
4.5528 
0.2777 

4.557 
0.4815 
1200 
4.4413 
0.2940 

4.2948 
0.5618 
1400 
4.3298 
0.3233 

4.2969 
0.6421 
1600 
4.2270 
0.3502 

4.0779 
0.7223 
1800 
4.1218 
0.3743 

4.0473 
0.8026 
2000 
4.0337 
0.3897 

4.0347 
0.8828 
2200 
3.9426 
0.3879 

3.9185 
0.9631 
2400 
3.8602 
0.4158 

3.5221 
1.0433 
2600 
3.7700 
0.4275 

3.5359 
1.1236 
2800 
3.6728 
0.4553 

3.4622 
1.2039 
3000 
3.5906 
0.4541 

3.431 
1.2841 
3200 
3.5025 
0.4732 

3.3443 
1.3644 
3400 
3.4168 
0.4869 

3.4344 
1.4446 
3600 
3.3382 
0.5025 

3.249 
1.5249 
3800 
3.2703 
0.5160 

3.2028 
1.6051 
4000 
3.2017 
0.4927 

3.0678 
1.6854 
4200 
3.1264 
0.5152 

3.0626 
1.7657 
4400 
3.0487 
0.5410 

2.953 
1.8459 
4600 
2.9699 
0.5414 

3.0011 
1.9262 
4800 
2.9165 
0.5503 

2.9428 
2.0064 
5000 
2.8433 
0.5665 

2.6717 
2.0867 
5200 
2.7818 
0.5569 

2.6253 
2.1669 
5400 
2.7195 
0.5715 

2.3998 
2.2472 
5600 
2.6458 
0.5874 

2.2518 
2.3274 
5800 
2.5901 
0.5922 

2.4229 
2.4077 
6000 
2.5301 
0.5912 

2.592 
2.4880 
6200 
2.4855 
0.5984 

2.0625 
2.5682 
6400 
2.4277 
0.6002 

2.22 
2.6485 
6600 
2.3784 
0.6087 

2.3326 
2.7287 
6800 
2.3250 
0.6123 

2.1592 
2.8090 
7000 
2.2958 
0.6095 

2.1491 
2.8892 
7200 
2.2226 
0.6303 

2.0644 
2.9695 
7400 
2.1923 
0.6231 

1.916 
3.0498 
7600 
2.1510 
0.6352 

1.7435 
3.1300 
7800 
2.0985 
0.6388 

1.761 
3.2103 
8000 
2.0753 
0.6404 

1.5321 
3.2905 
8200 
2.0396 
0.6426 

1.6117 
3.3708 
8400 
1.9855 
0.6530 

1.5593 
3.4510 
8600 
1.9805 
0.6352 

1.9288 
3.5313 
8800 
1.9188 
0.6564 

1.5736 
3.6116 
9000 
1.9141 
0.6556 

1.5544 
3.6918 
9200 
1.8633 
0.6619 

1.3811 
3.7721 
9400 
1.8466 
0.6621 

1.608 
3.8523 
9600 
1.8116 
0.6687 

1.533 
3.9326 
9800 
1.7784 
0.6733 

1.5496 
4.0128 
10000 
1.7532 
0.6755 

1.3532 
4.0931 
10200 
1.7399 
0.6779 

1.3787 
4.1734 
10400 
1.6996 
0.6795 

1.4278 
4.2536 
10600 
1.6893 
0.6771 

1.3531 
4.3339 
10800 
1.6629 
0.6759 

1.2811 
4.4141 
11000 
1.6493 
0.6801 

1.3787 
4.4944 
11200 
1.6278 
0.6855 

1.2663 
4.5746 
11400 
1.6101 
0.6926 

1.0892 
4.6549 
11600 
1.5842 
0.6887 

1.3045 
4.7352 
11800 
1.5758 
0.6911 

1.4239 
4.8154 
12000 
1.5647 
0.6930 

1.065 
4.8957 
12200 
1.5403 
0.6905 

1.1467 
4.9759 
12400 
1.5257 
0.6986 

0.8755 
5.0562 
12600 
1.5075 
0.6964 

1.0427 
5.1364 
12800 
1.4977 
0.7074 

1.264 
5.2167 
13000 
1.4951 
0.6956 

0.9822 
5.2970 
13200 
1.4787 
0.6990 

1.1234 
5.3772 
13400 
1.4673 
0.7008 

0.9394 
5.4575 
13600 
1.4632 
0.6998 

0.9231 
5.5377 
13800 
1.4346 
0.7074 

1.1829 
5.6180 
14000 
1.4364 
0.7092 

0.9687 
5.6982 
14200 
1.4231 
0.7080 

0.8915 
5.7785 
14400 
1.4166 
0.7104 

1.013 
5.8587 
14600 
1.4056 
0.7110 

1.0437 
5.9390 
14800 
1.3840 
0.7186 

0.8936 
6.0193 
15000 
1.3896 
0.7142 

0.8968 
6.0995 
15200 
1.3853 
0.7118 

0.8978 
6.1798 
15400 
1.3748 
0.7154 

0.8638 
6.2600 
15600 
1.3686 
0.7190 

0.7187 
6.3403 
15800 
1.3664 
0.7186 

0.7554 
6.4205 
16000 
1.3672 
0.7124 

0.7664 
6.5008 
16200 
1.3484 
0.7192 

0.9791 
6.5811 
16400 
1.3500 
0.7178 

0.8325 
6.6613 
16600 
1.3387 
0.7184 

1.0476 
6.7416 
16800 
1.3390 
0.7174 

0.7053 
6.8218 
17000 
1.3268 
0.7217 

0.9869 
6.9021 
17200 
1.3270 
0.7204 

0.8179 
6.9823 
17400 
1.3169 
0.7297 

0.9584 
7.0626 
17600 
1.3119 
0.7271 

0.6394 
7.1429 
17800 
1.3158 
0.7243 

0.9094 
7.2231 
18000 
1.3056 
0.7231 

0.7837 
7.3034 
18200 
1.3174 
0.7239 

0.7168 
7.3836 
18400 
1.3088 
0.7265 

0.8603 
7.4639 
18600 
1.3149 
0.7204 

0.6326 
7.5441 
18800 
1.3041 
0.7253 

0.8656 
7.6244 
19000 
1.3075 
0.7253 

0.7517 
7.7047 
19200 
1.3181 
0.7227 

0.8719 
7.7849 
19400 
1.2977 
0.7273 

0.6939 
7.8652 
19600 
1.2965 
0.7249 

0.8371 
7.9454 
19800 
1.3020 
0.7233