File size: 4,645 Bytes
a8fd5da dbf3f72 bce9afa a8fd5da dbf3f72 a8fd5da |
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 |
---
library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-large-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: CTMAE-P2-V4-S3
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. -->
# CTMAE-P2-V4-S3
This model is a fine-tuned version of [MCG-NJU/videomae-large-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-large-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 2.1094
- Accuracy: 0.7111
## 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: 1e-05
- train_batch_size: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_ratio: 0.1
- training_steps: 13050
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:-----:|:---------------:|:--------:|
| 1.5461 | 0.02 | 261 | 2.1854 | 0.5556 |
| 0.6074 | 1.02 | 522 | 2.6518 | 0.5556 |
| 1.5766 | 2.02 | 783 | 1.9843 | 0.5556 |
| 0.7713 | 3.02 | 1044 | 2.2332 | 0.5556 |
| 1.797 | 4.02 | 1305 | 1.7064 | 0.5556 |
| 0.8914 | 5.02 | 1566 | 1.8977 | 0.5556 |
| 0.7372 | 6.02 | 1827 | 2.2072 | 0.5556 |
| 1.0467 | 7.02 | 2088 | 1.7544 | 0.5556 |
| 1.2248 | 8.02 | 2349 | 2.0315 | 0.5556 |
| 0.7126 | 9.02 | 2610 | 1.7717 | 0.5556 |
| 1.2486 | 10.02 | 2871 | 2.0448 | 0.5556 |
| 2.2836 | 11.02 | 3132 | 2.1988 | 0.5556 |
| 0.8409 | 12.02 | 3393 | 1.6258 | 0.6444 |
| 0.4642 | 13.02 | 3654 | 1.3451 | 0.6667 |
| 0.007 | 14.02 | 3915 | 2.2438 | 0.5556 |
| 0.9377 | 15.02 | 4176 | 1.1871 | 0.6444 |
| 0.7025 | 16.02 | 4437 | 1.8905 | 0.6444 |
| 0.2657 | 17.02 | 4698 | 2.1760 | 0.6222 |
| 1.3937 | 18.02 | 4959 | 2.0622 | 0.6 |
| 1.9924 | 19.02 | 5220 | 1.8416 | 0.6667 |
| 0.0009 | 20.02 | 5481 | 1.9068 | 0.6444 |
| 1.0231 | 21.02 | 5742 | 1.8428 | 0.6667 |
| 0.7099 | 22.02 | 6003 | 2.3108 | 0.6 |
| 0.3243 | 23.02 | 6264 | 2.2084 | 0.5778 |
| 2.748 | 24.02 | 6525 | 1.8855 | 0.6889 |
| 0.0002 | 25.02 | 6786 | 1.9443 | 0.6667 |
| 1.1288 | 26.02 | 7047 | 1.6372 | 0.6444 |
| 0.0024 | 27.02 | 7308 | 2.0813 | 0.6444 |
| 1.3731 | 28.02 | 7569 | 2.1846 | 0.6444 |
| 0.0085 | 29.02 | 7830 | 2.2414 | 0.6222 |
| 0.0004 | 30.02 | 8091 | 2.5363 | 0.5778 |
| 0.7817 | 31.02 | 8352 | 2.8433 | 0.5778 |
| 0.3487 | 32.02 | 8613 | 2.6374 | 0.6444 |
| 0.0014 | 33.02 | 8874 | 3.0313 | 0.5778 |
| 0.0009 | 34.02 | 9135 | 2.6187 | 0.6667 |
| 0.014 | 35.02 | 9396 | 2.1094 | 0.7111 |
| 0.512 | 36.02 | 9657 | 2.1110 | 0.6667 |
| 0.0003 | 37.02 | 9918 | 3.0441 | 0.5778 |
| 0.0001 | 38.02 | 10179 | 2.4423 | 0.6889 |
| 0.0009 | 39.02 | 10440 | 2.3538 | 0.6889 |
| 0.0001 | 40.02 | 10701 | 2.4812 | 0.6667 |
| 0.0001 | 41.02 | 10962 | 2.5847 | 0.6667 |
| 0.0 | 42.02 | 11223 | 2.5525 | 0.6889 |
| 0.002 | 43.02 | 11484 | 2.6746 | 0.6889 |
| 0.0004 | 44.02 | 11745 | 2.4888 | 0.6667 |
| 0.0001 | 45.02 | 12006 | 2.5662 | 0.6444 |
| 0.0011 | 46.02 | 12267 | 2.5288 | 0.6667 |
| 0.0001 | 47.02 | 12528 | 2.5611 | 0.6667 |
| 0.7043 | 48.02 | 12789 | 2.7606 | 0.6667 |
| 0.0001 | 49.02 | 13050 | 2.7966 | 0.6667 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0
|