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Timesformer Wlasl 100 200ep CoR

This model is a fine-tuned version of facebook/timesformer-base-finetuned-k400 on an unknown dataset. It achieves the following results on the evaluation set: Loss: 2.5784 Accuracy: 0.5592

Quellehuggingface.co/Shawon16/timesformer_wlasl_100_200ep_coR_/tree/7eed1a04390044b6254920c5966e8ee0a6fce4da
ArtOtherBasismodellfacebook/timesformer-base-finetuned-k400VersionModelBBewertung

Modellquelle

Art
Other
Dateigröße
463 MB
Basismodell
facebook/timesformer-base-finetuned-k400
Version
vModel
Aktualisiert
24. Okt. 2026
Quelle
Hugging Face

Quellenbeschreibung

timesformer_wlasl_100_200ep_coR_

This model is a fine-tuned version of facebook/timesformer-base-finetuned-k400 on an unknown dataset. It achieves the following results on the evaluation set:

  • Loss: 2.5784
  • Accuracy: 0.5592

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
  • gradient_accumulation_steps: 4
  • total_train_batch_size: 8
  • optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
  • lr_scheduler_type: linear
  • lr_scheduler_warmup_ratio: 0.1
  • training_steps: 36000
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
18.90030.0051804.68680.0089
18.36931.00503604.53530.0414
17.24762.00505404.28350.0828
15.30513.00507213.89920.1598
12.95924.0059013.48290.2456
10.49345.005010813.15370.3491
8.25886.005012612.81150.4172
6.17657.005014422.56710.4438
4.3218.00516222.27920.5030
2.8749.005018022.10450.5296
1.763410.005019821.97380.5414
1.089111.005021631.89310.5592
0.699212.00523431.76060.5651
0.42913.005025231.68790.5799
0.32714.005027031.70750.5976
0.195915.005028841.64860.5917
0.158816.00530641.84400.5621
0.156317.005032441.73940.5888
0.191318.005034241.90170.5710
0.160319.005036051.95270.5828
0.100720.00537851.90930.6124
0.095221.005039651.80470.6036
0.083322.005041451.96310.5680
0.153723.005043261.92070.6154
0.219824.00545061.89790.5976
0.131625.005046861.91790.5917
0.150326.005048661.97430.5769
0.142927.005050472.04550.5740
0.098828.00552272.08440.5710
0.181929.005054072.05160.5947
0.118430.005055872.40840.5621
0.111331.005057682.27450.5473
0.138232.00559482.55050.5385
0.137533.005061282.29800.5592
0.241434.005063082.30810.5325
0.125535.005064892.13510.5858
0.102436.00566692.19040.6006
0.163937.005068492.25390.5740
0.162538.005070292.13300.5858
0.221639.005072102.41280.5503
0.164840.00573902.42920.5680
0.127641.005075702.37370.6036
0.087242.005077502.22010.6183
0.136643.005079312.35840.5917
0.069744.00581112.25360.5858
0.10945.005082912.13990.6095
0.111446.005084712.28590.5740
0.104347.005086522.42370.5592
0.099948.00588322.48050.5385
0.218449.005090122.30020.5740
0.177650.005091922.34140.5533
0.122251.005093732.38390.5888
0.068752.00595532.59900.5592
0.08653.005097332.60020.5799
0.040354.005099132.31520.5947
0.060355.0050100942.44020.5858
0.04456.005102742.34510.6124
0.119357.0050104542.51410.5680
0.106858.0050106342.64380.5828
0.072559.0050108152.51380.5858
0.11960.005109952.51380.5888
0.192761.0050111752.77760.5503
0.145862.0050113552.57840.5592

Framework versions

  • Transformers 4.46.1
  • Pytorch 2.5.1+cu124
  • Datasets 3.1.0
  • Tokenizers 0.20.1

Quellen

1 Quelle
Hugging FacePrimärVersion 7eed1a04390044b6254920c5966e8ee0a6fce4da
huggingface.co/Shawon16/timesformer_wlasl_100_200ep_coR_/tree/7eed1a04390044b6254920c5966e8ee0a6fce4da

Verifiziert 24. Okt.

Modellartefakte

1 Artefakt

model.safetensors

safetensors · 463 MB · SHA-256 f416aae3b902…3657 · Hugging Face

Download file

Quellenauszüge

2 Auszüge
Readme6. Aug.huggingface.co/Shawon16/timesformer_wlasl_100_200ep_coR_

--- library_name: transformers license: cc-by-nc-4.0 base_model: facebook/timesformer-base-finetuned-k400 tags: - generated_from_trainer metrics: - accuracy model-index: - name: timesformer_wlasl_100_200ep_coR_ 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. --> # timesformer_wlasl_100_200ep_coR_ This model is a fine-tuned version of [facebook/timesformer-base-finetuned-k400](https://huggingface.co/facebook/timesformer-base-finetuned-k400) on an unknown dataset. It achieves the following results on the evaluation set: - Loss: 2.5784 - Accuracy: 0.5592 ## 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 - gradient_accumulation_steps: 4 - total_train_batch_size: 8 - optimizer: Use adamw_torch with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments - lr_scheduler_type: linear - lr_scheduler_warmup_ratio: 0.1 - training_steps: 36000 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:-----:|:---------------:|:--------:| | 18.9003 | 0.005 | 180 | 4.6868 | 0.0089 | | 18.3693 | 1.0050 | 360 | 4.5353 | 0.0414 | | 17.2476 | 2.0050 | 540 | 4.2835 | 0.0828 | | 15.3051 | 3.0050 | 721 | 3.8992 | 0.1598 | | 12.9592 | 4.005 | 901 | 3.4829 | 0.2456 | | 10.4934 | 5.0050 | 1081 | 3.1537 | 0.3491 | | 8.2588 | 6.0050 | 1261 | 2.8115 | 0.4172 | | 6.1765 | 7.0050 | 1442 | 2.5671 | 0.4438 | | 4.321 | 8.005 | 1622 | 2.2792 | 0.5030 | | 2.874 | 9.0050 | 1802 | 2.1045 | 0.5296 | | 1.7634 | 10.0050 | 1982 | 1.9738 | 0.5414 | | 1.0891 | 11.0050 | 2163 | 1.8931 | 0.5592 | | 0.6992 | 12.005 | 2343 | 1.7606 | 0.5651 | | 0.429 | 13.0050 | 2523 | 1.6879 | 0.5799 | | 0.327 | 14.0050 | 2703 | 1.7075 | 0.5976 | | 0.1959 | 15.0050 | 2884 | 1.6486 | 0.5917 | | 0.1588 | 16.005 | 3064 | 1.8440 | 0.5621 | | 0.1563 | 17.0050 | 3244 | 1.7394 | 0.5888 | | 0.1913 | 18.0050 | 3424 | 1.9017 | 0.5710 | | 0.1603 | 19.0050 |...

Note6. Aug.huggingface.co/Shawon16/timesformer_wlasl_100_200ep_coR_

Source context: 8 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/timesformer_wlasl_100_200ep_coR_