videomae-base-finetuned-IEMOCAP_videos
This model is a fine-tuned version of MCG-NJU/videomae-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 1.3194
- Accuracy: 0.3761
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: 8
- eval_batch_size: 8
- 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: 4070
Training results
Training Loss | Epoch | Step | Validation Loss | Accuracy |
---|---|---|---|---|
1.4161 | 0.1 | 408 | 1.4228 | 0.2115 |
1.3522 | 1.1 | 816 | 1.3968 | 0.2363 |
1.2575 | 2.1 | 1224 | 1.4228 | 0.3115 |
1.2897 | 3.1 | 1632 | 1.4101 | 0.2984 |
1.3398 | 4.1 | 2040 | 1.4176 | 0.2599 |
1.3621 | 5.1 | 2448 | 1.3590 | 0.2830 |
1.2824 | 6.1 | 2856 | 1.3133 | 0.3610 |
1.3064 | 7.1 | 3264 | 1.3195 | 0.3077 |
1.378 | 8.1 | 3672 | 1.3562 | 0.2643 |
1.1909 | 9.1 | 4070 | 1.3917 | 0.2621 |
Framework versions
- Transformers 4.29.1
- Pytorch 2.0.0+cu118
- Datasets 2.12.0
- Tokenizers 0.13.3
- Downloads last month
- 2
This model does not have enough activity to be deployed to Inference API (serverless) yet. Increase its social
visibility and check back later, or deploy to Inference Endpoints (dedicated)
instead.