File size: 5,502 Bytes
2093040 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 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 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 |
---
license: cc-by-nc-4.0
base_model: facebook/timesformer-base-finetuned-k400
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: tsf-gs-rot-flip-wtoken-DRPT-r128-f150-8.8-h768-i3072-p32-b8-e60
results: []
---
<!-- This model card has been generated automatically according to the information the Trainer had access to. You
should probably proofread and complete it, then remove this comment. -->
# tsf-gs-rot-flip-wtoken-DRPT-r128-f150-8.8-h768-i3072-p32-b8-e60
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: 0.7740
- Accuracy: 0.8610
## 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: 6480
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 1.1114 | 0.0168 | 109 | 1.0984 | 0.3797 |
| 1.1049 | 1.0168 | 218 | 1.1141 | 0.3262 |
| 1.1056 | 2.0168 | 327 | 1.1710 | 0.3262 |
| 1.1154 | 3.0168 | 436 | 1.1256 | 0.3369 |
| 1.1056 | 4.0168 | 545 | 1.0962 | 0.3529 |
| 1.1569 | 5.0168 | 654 | 1.1136 | 0.3262 |
| 1.036 | 6.0168 | 763 | 1.0213 | 0.4652 |
| 1.0506 | 7.0168 | 872 | 1.0488 | 0.4278 |
| 1.042 | 8.0168 | 981 | 0.9366 | 0.5561 |
| 0.8999 | 9.0168 | 1090 | 0.8098 | 0.6310 |
| 0.9432 | 10.0168 | 1199 | 0.9513 | 0.5936 |
| 0.7898 | 11.0168 | 1308 | 0.5836 | 0.8021 |
| 0.7952 | 12.0168 | 1417 | 0.5680 | 0.7647 |
| 0.6641 | 13.0168 | 1526 | 0.6147 | 0.7861 |
| 0.6901 | 14.0168 | 1635 | 0.5688 | 0.7754 |
| 0.4637 | 15.0168 | 1744 | 0.5834 | 0.7914 |
| 0.5898 | 16.0168 | 1853 | 0.6636 | 0.7326 |
| 0.7036 | 17.0168 | 1962 | 0.7142 | 0.7433 |
| 0.3946 | 18.0168 | 2071 | 0.4866 | 0.8342 |
| 0.5379 | 19.0168 | 2180 | 0.6641 | 0.7701 |
| 0.5869 | 20.0168 | 2289 | 0.4817 | 0.8289 |
| 0.4564 | 21.0168 | 2398 | 0.4909 | 0.8396 |
| 0.419 | 22.0168 | 2507 | 0.5006 | 0.8235 |
| 0.4989 | 23.0168 | 2616 | 0.5648 | 0.8182 |
| 0.2701 | 24.0168 | 2725 | 0.5963 | 0.8342 |
| 0.5191 | 25.0168 | 2834 | 0.5766 | 0.7914 |
| 0.5088 | 26.0168 | 2943 | 0.4679 | 0.8610 |
| 0.3828 | 27.0168 | 3052 | 0.5231 | 0.8503 |
| 0.4228 | 28.0168 | 3161 | 0.6142 | 0.8235 |
| 0.5544 | 29.0168 | 3270 | 0.6508 | 0.8289 |
| 0.3595 | 30.0168 | 3379 | 0.6572 | 0.7914 |
| 0.3117 | 31.0168 | 3488 | 0.5587 | 0.8342 |
| 0.3324 | 32.0168 | 3597 | 0.5021 | 0.8610 |
| 0.3282 | 33.0168 | 3706 | 0.7642 | 0.8235 |
| 0.427 | 34.0168 | 3815 | 0.5739 | 0.8663 |
| 0.152 | 35.0168 | 3924 | 0.6957 | 0.8610 |
| 0.426 | 36.0168 | 4033 | 0.6705 | 0.8342 |
| 0.2803 | 37.0168 | 4142 | 0.5854 | 0.8449 |
| 0.3198 | 38.0168 | 4251 | 0.5280 | 0.8449 |
| 0.4348 | 39.0168 | 4360 | 0.7755 | 0.8128 |
| 0.1915 | 40.0168 | 4469 | 0.6813 | 0.8503 |
| 0.0793 | 41.0168 | 4578 | 0.7260 | 0.8503 |
| 0.3902 | 42.0168 | 4687 | 0.6581 | 0.8663 |
| 0.3552 | 43.0168 | 4796 | 0.5732 | 0.8610 |
| 0.3091 | 44.0168 | 4905 | 0.7510 | 0.8396 |
| 0.1103 | 45.0168 | 5014 | 0.7604 | 0.8503 |
| 0.3362 | 46.0168 | 5123 | 0.7156 | 0.8556 |
| 0.1935 | 47.0168 | 5232 | 0.6882 | 0.8503 |
| 0.0889 | 48.0168 | 5341 | 0.7639 | 0.8663 |
| 0.2156 | 49.0168 | 5450 | 0.8250 | 0.8610 |
| 0.0949 | 50.0168 | 5559 | 0.8256 | 0.8556 |
| 0.1735 | 51.0168 | 5668 | 0.6839 | 0.8770 |
| 0.1612 | 52.0168 | 5777 | 0.9082 | 0.8663 |
| 0.0556 | 53.0168 | 5886 | 0.7659 | 0.8770 |
| 0.0997 | 54.0168 | 5995 | 0.8025 | 0.8824 |
| 0.1648 | 55.0168 | 6104 | 0.8449 | 0.8770 |
| 0.1443 | 56.0168 | 6213 | 0.7801 | 0.8770 |
| 0.0405 | 57.0168 | 6322 | 0.8647 | 0.8663 |
| 0.3323 | 58.0168 | 6431 | 0.8411 | 0.8503 |
| 0.1137 | 59.0076 | 6480 | 0.7740 | 0.8610 |
### Framework versions
- Transformers 4.41.2
- Pytorch 1.13.0+cu117
- Datasets 2.20.0
- Tokenizers 0.19.1
|