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library_name: transformers
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: shot_model
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. -->
# shot_model
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: 1.4299
- Accuracy: 0.692
## 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: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 0.1
- training_steps: 6250
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.6227 | 1.0 | 625 | 1.9235 | 0.228 |
| 1.4269 | 2.0 | 1250 | 1.4425 | 0.496 |
| 1.0222 | 3.0 | 1875 | 1.3376 | 0.5 |
| 1.0616 | 4.0 | 2500 | 1.6164 | 0.464 |
| 1.0547 | 5.0 | 3125 | 1.2287 | 0.552 |
| 0.6092 | 6.0 | 3750 | 1.3996 | 0.584 |
| 0.5217 | 7.0 | 4375 | 1.2899 | 0.644 |
| 0.7761 | 8.0 | 5000 | 1.5018 | 0.656 |
| 1.2009 | 9.0 | 5625 | 1.4867 | 0.676 |
| 0.2304 | 10.0 | 6250 | 1.4299 | 0.692 |
### Framework versions
- Transformers 5.3.0
- Pytorch 2.10.0
- Datasets 4.6.1
- Tokenizers 0.22.2
|