metadata

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: []

videomae-base-finetuned-kinetics-fight_18-03-2024

This model is a fine-tuned version of 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