File size: 4,696 Bytes
628f4a7 |
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-V2-S2
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-V2-S2
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: 1.5069
- Accuracy: 0.7333
## 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: 2
- eval_batch_size: 2
- 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: 6500
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-------:|:----:|:---------------:|:--------:|
| 0.6135 | 0.0202 | 131 | 0.7942 | 0.5556 |
| 0.4654 | 1.0202 | 262 | 2.2124 | 0.5556 |
| 1.1122 | 2.0202 | 393 | 1.8386 | 0.5556 |
| 0.7797 | 3.0202 | 524 | 0.9344 | 0.5556 |
| 1.379 | 4.0202 | 655 | 1.5755 | 0.5556 |
| 0.7305 | 5.0202 | 786 | 1.4677 | 0.5556 |
| 0.9115 | 6.0202 | 917 | 1.5456 | 0.5556 |
| 1.6622 | 7.0202 | 1048 | 1.2113 | 0.5556 |
| 0.6868 | 8.0202 | 1179 | 1.8451 | 0.5556 |
| 1.199 | 9.0202 | 1310 | 1.3622 | 0.5556 |
| 0.7459 | 10.0202 | 1441 | 1.4034 | 0.5556 |
| 0.5574 | 11.0202 | 1572 | 0.9836 | 0.5556 |
| 0.3742 | 12.0202 | 1703 | 0.6934 | 0.6889 |
| 0.3303 | 13.0202 | 1834 | 0.7161 | 0.6889 |
| 0.8856 | 14.0202 | 1965 | 1.5608 | 0.5556 |
| 0.186 | 15.0202 | 2096 | 0.7782 | 0.6 |
| 0.7263 | 16.0202 | 2227 | 1.4438 | 0.5778 |
| 1.552 | 17.0202 | 2358 | 1.2117 | 0.6222 |
| 0.1031 | 18.0202 | 2489 | 1.2174 | 0.6667 |
| 1.193 | 19.0202 | 2620 | 1.2043 | 0.6444 |
| 0.322 | 20.0202 | 2751 | 1.3639 | 0.6444 |
| 0.3791 | 21.0202 | 2882 | 1.3107 | 0.6444 |
| 0.6201 | 22.0202 | 3013 | 1.2797 | 0.6889 |
| 0.9547 | 23.0202 | 3144 | 1.1654 | 0.6444 |
| 1.4286 | 24.0202 | 3275 | 1.4078 | 0.6667 |
| 0.6023 | 25.0202 | 3406 | 1.5069 | 0.7333 |
| 0.2925 | 26.0202 | 3537 | 1.4529 | 0.6889 |
| 0.1445 | 27.0202 | 3668 | 1.4417 | 0.7333 |
| 0.2717 | 28.0202 | 3799 | 2.1237 | 0.6444 |
| 0.411 | 29.0202 | 3930 | 1.5399 | 0.6889 |
| 0.6632 | 30.0202 | 4061 | 1.6289 | 0.7333 |
| 0.3 | 31.0202 | 4192 | 1.9944 | 0.6222 |
| 0.386 | 32.0202 | 4323 | 1.9271 | 0.6889 |
| 0.1569 | 33.0202 | 4454 | 1.8172 | 0.6889 |
| 0.2135 | 34.0202 | 4585 | 1.7862 | 0.6889 |
| 0.3142 | 35.0202 | 4716 | 1.6904 | 0.7111 |
| 0.2179 | 36.0202 | 4847 | 1.9549 | 0.7111 |
| 0.7634 | 37.0202 | 4978 | 1.9367 | 0.6889 |
| 0.0008 | 38.0202 | 5109 | 1.9890 | 0.6667 |
| 0.1467 | 39.0202 | 5240 | 1.9472 | 0.6889 |
| 0.6641 | 40.0202 | 5371 | 2.2295 | 0.6889 |
| 0.3125 | 41.0202 | 5502 | 1.8309 | 0.7111 |
| 0.1987 | 42.0202 | 5633 | 2.1643 | 0.6889 |
| 0.067 | 43.0202 | 5764 | 2.1776 | 0.6667 |
| 0.1513 | 44.0202 | 5895 | 2.1978 | 0.6667 |
| 0.0032 | 45.0202 | 6026 | 1.9291 | 0.7333 |
| 0.2596 | 46.0202 | 6157 | 2.0961 | 0.6889 |
| 0.0006 | 47.0202 | 6288 | 2.0126 | 0.7111 |
| 0.0305 | 48.0202 | 6419 | 2.0029 | 0.7333 |
| 0.0004 | 49.0125 | 6500 | 2.0025 | 0.7333 |
### Framework versions
- Transformers 4.46.2
- Pytorch 2.0.1+cu117
- Datasets 3.0.1
- Tokenizers 0.20.0
|