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---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base-finetuned-kinetics
tags:
- generated_from_trainer
metrics:
- accuracy
- precision
- recall
model-index:
- name: videomae-base-finetuned-kinetics-fight_18-03-2024
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-finetuned-kinetics-fight_18-03-2024
This model is a fine-tuned version of [MCG-NJU/videomae-base-finetuned-kinetics](https://huggingface.co/MCG-NJU/videomae-base-finetuned-kinetics) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.2211
- Accuracy: 0.9175
- Precision: 0.9372
- Recall: 0.895
## 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-07
- train_batch_size: 12
- eval_batch_size: 12
- 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: 2660
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall |
|:-------------:|:-----:|:----:|:---------------:|:--------:|:---------:|:------:|
| 0.7318 | 0.05 | 134 | 0.7169 | 0.43 | 0.4247 | 0.395 |
| 0.6646 | 1.05 | 268 | 0.6636 | 0.59 | 0.6139 | 0.485 |
| 0.6089 | 2.05 | 402 | 0.5944 | 0.78 | 0.8415 | 0.69 |
| 0.5485 | 3.05 | 536 | 0.5270 | 0.845 | 0.8920 | 0.785 |
| 0.4581 | 4.05 | 670 | 0.4630 | 0.865 | 0.9011 | 0.82 |
| 0.3436 | 5.05 | 804 | 0.3994 | 0.8725 | 0.9162 | 0.82 |
| 0.3109 | 6.05 | 938 | 0.3530 | 0.8775 | 0.9171 | 0.83 |
| 0.2672 | 7.05 | 1072 | 0.3212 | 0.88 | 0.9176 | 0.835 |
| 0.2243 | 8.05 | 1206 | 0.2947 | 0.895 | 0.9202 | 0.865 |
| 0.297 | 9.05 | 1340 | 0.2779 | 0.895 | 0.9202 | 0.865 |
| 0.21 | 10.05 | 1474 | 0.2615 | 0.9025 | 0.9215 | 0.88 |
| 0.2003 | 11.05 | 1608 | 0.2515 | 0.895 | 0.9202 | 0.865 |
| 0.2128 | 12.05 | 1742 | 0.2418 | 0.91 | 0.9271 | 0.89 |
| 0.1789 | 13.05 | 1876 | 0.2357 | 0.9125 | 0.9275 | 0.895 |
| 0.1672 | 14.05 | 2010 | 0.2300 | 0.91 | 0.9227 | 0.895 |
| 0.1532 | 15.05 | 2144 | 0.2275 | 0.9175 | 0.9372 | 0.895 |
| 0.1695 | 16.05 | 2278 | 0.2241 | 0.9125 | 0.9275 | 0.895 |
| 0.1255 | 17.05 | 2412 | 0.2225 | 0.915 | 0.9323 | 0.895 |
| 0.1168 | 18.05 | 2546 | 0.2214 | 0.9175 | 0.9372 | 0.895 |
| 0.1395 | 19.04 | 2660 | 0.2211 | 0.9175 | 0.9372 | 0.895 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.0.1+cu118
- Datasets 2.18.0
- Tokenizers 0.15.2
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