--- license: cc-by-nc-4.0 base_model: facebook/timesformer-base-finetuned-k400 tags: - generated_from_trainer metrics: - accuracy model-index: - name: tsf-newDS-DRPT-r224-f90-8.8-h768-i3072-p32-b8-e100 results: [] --- # tsf-newDS-DRPT-r224-f90-8.8-h768-i3072-p32-b8-e100 This model is a fine-tuned version of [facebook/timesformer-base-finetuned-k400](https://huggingface.co/facebook/timesformer-base-finetuned-k400) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 1.4780 - Accuracy: 0.7478 ## Model description More information needed ## Intended uses & limitations More information needed ## Training and evaluation data More information needed ## Training procedure ### Training hyperparameters The following hyperparameters were used during training: - learning_rate: 5e-05 - train_batch_size: 8 - eval_batch_size: 8 - seed: 42 - optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08 - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 13100 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-----:|:-----:|:---------------:|:--------:| | 1.1939 | 0.01 | 131 | 1.1309 | 0.3673 | | 1.1355 | 1.01 | 262 | 1.1368 | 0.3230 | | 1.0944 | 2.01 | 393 | 1.1001 | 0.3628 | | 1.151 | 3.01 | 524 | 1.1368 | 0.3540 | | 1.1259 | 4.01 | 655 | 1.1324 | 0.3230 | | 1.1406 | 5.01 | 786 | 1.0984 | 0.3540 | | 1.1126 | 6.01 | 917 | 1.0994 | 0.3540 | | 1.1169 | 7.01 | 1048 | 1.1456 | 0.3230 | | 1.1217 | 8.01 | 1179 | 1.1333 | 0.3230 | | 1.1227 | 9.01 | 1310 | 1.1024 | 0.3230 | | 1.1136 | 10.01 | 1441 | 1.1115 | 0.3540 | | 1.0942 | 11.01 | 1572 | 1.0910 | 0.3142 | | 1.1089 | 12.01 | 1703 | 1.0973 | 0.3540 | | 1.1148 | 13.01 | 1834 | 1.1086 | 0.3496 | | 1.1019 | 14.01 | 1965 | 1.0919 | 0.3540 | | 1.1264 | 15.01 | 2096 | 1.1035 | 0.3540 | | 1.1235 | 16.01 | 2227 | 1.0961 | 0.3540 | | 1.1438 | 17.01 | 2358 | 1.0864 | 0.3584 | | 1.1092 | 18.01 | 2489 | 1.0938 | 0.3319 | | 1.111 | 19.01 | 2620 | 1.1190 | 0.3496 | | 1.0871 | 20.01 | 2751 | 1.1039 | 0.3584 | | 1.0632 | 21.01 | 2882 | 1.1465 | 0.3673 | | 1.0743 | 22.01 | 3013 | 1.1446 | 0.3628 | | 1.0811 | 23.01 | 3144 | 1.1103 | 0.3584 | | 1.1378 | 24.01 | 3275 | 1.1192 | 0.3628 | | 1.0274 | 25.01 | 3406 | 1.1488 | 0.3230 | | 1.0446 | 26.01 | 3537 | 1.1257 | 0.3407 | | 1.1225 | 27.01 | 3668 | 1.1199 | 0.3363 | | 1.0504 | 28.01 | 3799 | 1.1628 | 0.3496 | | 1.1138 | 29.01 | 3930 | 1.1905 | 0.3319 | | 1.066 | 30.01 | 4061 | 1.1344 | 0.3407 | | 1.0567 | 31.01 | 4192 | 1.1359 | 0.4027 | | 1.011 | 32.01 | 4323 | 1.1819 | 0.3628 | | 1.0595 | 33.01 | 4454 | 1.1846 | 0.3761 | | 1.028 | 34.01 | 4585 | 1.2150 | 0.3717 | | 1.045 | 35.01 | 4716 | 1.1456 | 0.3496 | | 1.0459 | 36.01 | 4847 | 1.0731 | 0.4646 | | 1.0581 | 37.01 | 4978 | 1.2463 | 0.4292 | | 0.9436 | 38.01 | 5109 | 1.1388 | 0.4425 | | 0.9794 | 39.01 | 5240 | 1.1613 | 0.4513 | | 0.8882 | 40.01 | 5371 | 1.1544 | 0.4381 | | 1.0316 | 41.01 | 5502 | 1.0461 | 0.4779 | | 0.8349 | 42.01 | 5633 | 1.0396 | 0.5088 | | 0.8478 | 43.01 | 5764 | 1.0630 | 0.5442 | | 0.8072 | 44.01 | 5895 | 1.1215 | 0.5177 | | 0.7213 | 45.01 | 6026 | 1.1616 | 0.6018 | | 0.7108 | 46.01 | 6157 | 1.1122 | 0.6106 | | 0.6225 | 47.01 | 6288 | 1.1400 | 0.6106 | | 0.5557 | 48.01 | 6419 | 0.9576 | 0.6283 | | 0.4944 | 49.01 | 6550 | 1.3350 | 0.5487 | | 0.7068 | 50.01 | 6681 | 0.9125 | 0.6504 | | 0.5947 | 51.01 | 6812 | 2.0044 | 0.4956 | | 0.645 | 52.01 | 6943 | 1.1295 | 0.5796 | | 0.4251 | 53.01 | 7074 | 1.7297 | 0.5 | | 0.573 | 54.01 | 7205 | 0.9968 | 0.6372 | | 0.4283 | 55.01 | 7336 | 1.1135 | 0.6195 | | 0.6225 | 56.01 | 7467 | 0.8792 | 0.7212 | | 0.3876 | 57.01 | 7598 | 1.3363 | 0.6150 | | 0.4729 | 58.01 | 7729 | 1.2033 | 0.6460 | | 0.4922 | 59.01 | 7860 | 1.0137 | 0.6593 | | 0.3925 | 60.01 | 7991 | 1.5002 | 0.6106 | | 0.4234 | 61.01 | 8122 | 1.3914 | 0.6018 | | 0.3847 | 62.01 | 8253 | 1.2090 | 0.6460 | | 0.3739 | 63.01 | 8384 | 1.1537 | 0.6549 | | 0.4808 | 64.01 | 8515 | 1.0365 | 0.7124 | | 0.2926 | 65.01 | 8646 | 1.2063 | 0.6814 | | 0.5116 | 66.01 | 8777 | 0.9150 | 0.7301 | | 0.34 | 67.01 | 8908 | 1.1562 | 0.6903 | | 0.452 | 68.01 | 9039 | 1.2344 | 0.6947 | | 0.2936 | 69.01 | 9170 | 2.3964 | 0.5088 | | 0.3911 | 70.01 | 9301 | 1.4071 | 0.6327 | | 0.19 | 71.01 | 9432 | 1.3819 | 0.6991 | | 0.3191 | 72.01 | 9563 | 1.7279 | 0.6460 | | 0.2172 | 73.01 | 9694 | 1.2274 | 0.7257 | | 0.2871 | 74.01 | 9825 | 1.4077 | 0.6947 | | 0.3536 | 75.01 | 9956 | 1.2094 | 0.7301 | | 0.2616 | 76.01 | 10087 | 1.7737 | 0.6372 | | 0.3808 | 77.01 | 10218 | 1.7553 | 0.6549 | | 0.3956 | 78.01 | 10349 | 1.3767 | 0.7035 | | 0.2217 | 79.01 | 10480 | 1.2784 | 0.7035 | | 0.3449 | 80.01 | 10611 | 1.0742 | 0.7611 | | 0.3193 | 81.01 | 10742 | 1.1135 | 0.7566 | | 0.3241 | 82.01 | 10873 | 1.3711 | 0.7345 | | 0.1948 | 83.01 | 11004 | 1.1718 | 0.7389 | | 0.4882 | 84.01 | 11135 | 1.1333 | 0.7655 | | 0.3604 | 85.01 | 11266 | 1.1587 | 0.7566 | | 0.3536 | 86.01 | 11397 | 1.4604 | 0.6947 | | 0.3896 | 87.01 | 11528 | 1.7899 | 0.6770 | | 0.2398 | 88.01 | 11659 | 1.3172 | 0.7566 | | 0.252 | 89.01 | 11790 | 1.7039 | 0.6858 | | 0.1858 | 90.01 | 11921 | 2.2136 | 0.6195 | | 0.2268 | 91.01 | 12052 | 1.4825 | 0.6991 | | 0.2984 | 92.01 | 12183 | 1.5829 | 0.6858 | | 0.1323 | 93.01 | 12314 | 1.5580 | 0.6947 | | 0.3251 | 94.01 | 12445 | 1.4773 | 0.7522 | | 0.1103 | 95.01 | 12576 | 1.7728 | 0.6460 | | 0.2054 | 96.01 | 12707 | 1.6074 | 0.6681 | | 0.2131 | 97.01 | 12838 | 1.9007 | 0.6770 | | 0.0364 | 98.01 | 12969 | 1.5574 | 0.6947 | | 0.1295 | 99.01 | 13100 | 1.4780 | 0.7478 | ### Framework versions - Transformers 4.41.2 - Pytorch 1.13.0+cu117 - Datasets 2.20.0 - Tokenizers 0.19.1