videomae-base-finetuned-isl-numbers_2

### Hiperparámetros de entrenamiento
Los siguientes hiperparámetros fueron usados durante el entrenamiento:

- learning_rate: 5e-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: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 3800

### Resultados del entrenamiento

| Pérdida del entrenamiento | Época | Paso | Pérdida de validación | Precisión |
|---------------------------|-------|------|----------------------|-----------|
| 3.5502                    | 0.02  | 76   | 3.4251               | 0.0945    |
| 3.1152                    | 1.02  | 152  | 3.0364               | 0.2756    |
| 2.6365                    | 2.02  | 228  | 2.6197               | 0.3780    |
| 2.3879                    | 3.02  | 304  | 2.1519               | 0.4646    |
| 1.9396                    | 4.02  | 380  | 2.0804               | 0.4173    |
| 1.9285                    | 5.02  | 456  | 1.9335               | 0.4488    |
| 1.5843                    | 6.02  | 532  | 1.7907               | 0.4803    |
| 1.2387                    | 7.02  | 608  | 1.8962               | 0.3858    |
| 1.2578                    | 8.02  | 684  | 1.7191               | 0.4488    |
| 0.9611                    | 9.02  | 760  | 1.7362               | 0.4882    |
| 0.9247                    | 10.02 | 836  | 1.3898               | 0.5906    |
| 0.8107                    | 11.02 | 912  | 1.9588               | 0.4094    |
| 0.7618                    | 12.02 | 988  | 1.1416               | 0.6614    |
| 0.7083                    | 13.02 | 1064 | 1.2812               | 0.6614    |
| 0.7098                    | 14.02 | 1140 | 1.4601               | 0.5197    |
| 0.4601                    | 15.02 | 1216 | 1.1276               | 0.6693    |
| 0.5684                    | 16.02 | 1292 | 1.4792               | 0.5591    |
| 0.5044                    | 17.02 | 1368 | 1.1236               | 0.6614    |
| 0.4551                    | 18.02 | 1444 | 1.3894               | 0.6063    |
| 0.3488                    | 19.02 | 1520 | 1.2918               | 0.6614    |
| 0.4711                    | 20.02 | 1596 | 1.2510               | 0.6299    |
| 0.3451                    | 21.02 | 1672 | 1.1265               | 0.6693    |
| 0.394                     | 22.02 | 1748 | 1.1676               | 0.6378    |
| 0.234                     | 23.02 | 1824 | 1.0714               | 0.7087    |
| 0.2318                    | 24.02 | 1900 | 1.2647               | 0.6378    |
| 0.4294                    | 25.02 | 1976 | 1.0250               | 0.7480    |
| 0.2084                    | 26.02 | 2052 | 1.1361               | 0.6850    |
| 0.1724                    | 27.02 | 2128 | 0.8791               | 0.7402    |
| 0.1715                    | 28.02 | 2204 | 0.7549               | 0.7559    |
| 0.2719                    | 29.02 | 2280 | 0.7708               | 0.7717    |
| 0.2021                    | 30.02 | 2356 | 1.1394               | 0.7165    |
| 0.0999                    | 31.02 | 2432 | 0.7838               | 0.7717    |
| 0.1473                    | 32.02 | 2508 | 1.3809               | 0.6457    |
| 0.0939                    | 33.02 | 2584 | 0.7839               | 0.7874    |
| 0.0952                    | 34.02 | 2660 | 1.0636               | 0.7008    |
| 0.2684                    | 35.02 | 2736 | 0.9194               | 0.7323    |
| 0.1628                    | 36.02 | 2812 | 0.7346               | 0.8031    |
| 0.0584                    | 37.02 | 2888 | 1.0112               | 0.7323    |
| 0.0567                    | 38.02 | 2964 | 1.0584               | 0.7323    |
| 0.1358                    | 39.02 | 3040 | 1.0566               | 0.7323    |
| 0.0796                    | 40.02 | 3116 | 0.9323               | 0.7480    |
| 0.0828                    | 41.02 | 3192 | 0.7611               | 0.7953    |
| 0.0661                    | 42.02 | 3268 | 0.7284               | 0.7874    |
| 0.0882                    | 43.02 | 3344 | 0.6982               | 0.7953    |
| 0.0398                    | 44.02 | 3420 | 0.8586               | 0.7717    |
| 0.2085                    | 45.02 | 3496 | 0.7990               | 0.7717    |
| 0.0509                    | 46.02 | 3572 | 0.7134               | 0.8268    |
| 0.0791                    | 47.02 | 3648 | 0.6887               | 0.8189    |
| 0.0469                    | 48.02 | 3724 | 0.7159               | 0.8031    |
| 0.0621                    | 49.02 | 3800 | 0.7062               | 0.8031    |

### Versiones del framework

- Transformers 4.40.0
- Pytorch 2.1.0+cu121
- Datasets 2.18.0
- Tokenizers 0.19.1