File size: 2,005 Bytes
6639a5d |
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 |
---
license: cc-by-nc-4.0
base_model: MCG-NJU/videomae-base
tags:
- generated_from_trainer
metrics:
- accuracy
model-index:
- name: videomae-base-finetuned-IEMOCAP_1xx
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-IEMOCAP_1xx
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: 4.2253
- Accuracy: 0.3303
## 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: 4440
### Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy |
|:-------------:|:-----:|:----:|:---------------:|:--------:|
| 1.2487 | 0.1 | 445 | 1.5638 | 0.3912 |
| 0.6787 | 1.1 | 890 | 1.1789 | 0.4877 |
| 0.7851 | 2.1 | 1335 | 0.9786 | 0.5811 |
| 0.3104 | 3.1 | 1780 | 1.1209 | 0.6273 |
| 0.5358 | 4.1 | 2225 | 0.8696 | 0.7084 |
| 0.3483 | 5.1 | 2670 | 1.0214 | 0.7084 |
| 0.3458 | 6.1 | 3115 | 1.0766 | 0.7125 |
| 0.2962 | 7.1 | 3560 | 1.2876 | 0.7351 |
| 0.0641 | 8.1 | 4005 | 1.3037 | 0.7382 |
| 0.0131 | 9.1 | 4440 | 1.3754 | 0.7474 |
### Framework versions
- Transformers 4.34.0
- Pytorch 1.12.0+cu116
- Datasets 2.14.5
- Tokenizers 0.14.1
|