File size: 2,384 Bytes
bd3e901 6f582a9 bd3e901 6f582a9 bd3e901 6f582a9 bd3e901 6f582a9 bd3e901 6f582a9 bd3e901 |
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 |
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-groub2-finetuned-SLT-subset
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. -->
# videomae-base-groub2-finetuned-SLT-subset
This model is a fine-tuned version of [MCG-NJU/videomae-base](https://huggingface.co/MCG-NJU/videomae-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2405
- Accuracy: 1.0
## 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: 2
- eval_batch_size: 2
- 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: 960
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 3.928 | 0.06 | 61 | 3.6624 | 0.0244 |
| 3.8332 | 1.06 | 122 | 3.5354 | 0.0732 |
| 3.5587 | 2.06 | 183 | 3.2996 | 0.0976 |
| 3.4907 | 3.06 | 244 | 3.1796 | 0.0976 |
| 3.4674 | 4.06 | 305 | 3.1159 | 0.0976 |
| 3.5079 | 5.06 | 366 | 3.0202 | 0.1220 |
| 2.9034 | 6.06 | 427 | 2.8292 | 0.1707 |
| 2.9286 | 7.06 | 488 | 2.4582 | 0.6098 |
| 2.4388 | 8.06 | 549 | 1.8469 | 0.7317 |
| 1.7172 | 9.06 | 610 | 1.2915 | 0.8537 |
| 1.2504 | 10.06 | 671 | 0.8991 | 0.9512 |
| 0.974 | 11.06 | 732 | 0.5943 | 0.9268 |
| 0.4528 | 12.06 | 793 | 0.4040 | 0.9512 |
| 0.3593 | 13.06 | 854 | 0.3052 | 1.0 |
| 0.2068 | 14.06 | 915 | 0.2569 | 1.0 |
| 0.185 | 15.05 | 960 | 0.2405 | 1.0 |
### Framework versions
- Transformers 4.33.3
- Pytorch 2.0.1+cu118
- Datasets 2.14.5
- Tokenizers 0.13.3
|