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Timesformer Wlasl 100 20ep 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: 1.4422 Accuracy: 0.6657

Sourcehuggingface.co/Shawon16/timesformer_wlasl_100_20ep_coR_/tree/b6c2bde988f7e4d462ac7676dc6098cbf2a271f8
TypeOtherModèle de basefacebook/timesformer-base-finetuned-k400VersionRevision b6c2bdeBClasse

Source du modèle

Type
Other
Taille du fichier
463 MB
Modèle de base
facebook/timesformer-base-finetuned-k400
Version
vRevision b6c2bde
Mis à jour
24 oct. 2026
Téléchargements
12
Source
Hugging Face

Description de la source

timesformer_wlasl_100_20ep_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: 1.4422
  • Accuracy: 0.6657

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: 3600
  • mixed_precision_training: Native AMP

Training results

Training LossEpochStepValidation LossAccuracy
18.5160.051804.32680.0680
14.62821.04993603.23820.3077
9.19832.04995402.51090.4379
5.2173.05017212.04610.5148
2.68584.059011.77170.5769
1.28845.049910811.67580.6006
0.64686.049912611.52350.6213
0.33987.050114421.44980.6272
0.18048.0516221.47020.6272
0.11199.049918021.41630.6302
0.07910.049919821.42690.6538
0.068611.050121631.40970.6568
0.062612.0523431.38780.6657
0.048513.049925231.45280.6686
0.061314.049927031.43480.6627
0.05315.050128841.40800.6716
0.043516.0530641.43310.6627
0.02917.049932441.44460.6568
0.029218.049934241.44390.6686
0.019919.048736001.44220.6657

Framework versions

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

Sources

1 source
Hugging FacePrincipalVersion b6c2bde988f7e4d462ac7676dc6098cbf2a271f8
huggingface.co/Shawon16/timesformer_wlasl_100_20ep_coR_/tree/b6c2bde988f7e4d462ac7676dc6098cbf2a271f8

Vérifié 24 oct.

Artefacts du modèle

1 artefact

model.safetensors

safetensors · 463 MB · SHA-256 f8058983ab0a…35bb · Hugging Face

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Extraits de sources

3 extraits
Readme6 aoûthuggingface.co/Shawon16/timesformer_wlasl_100_20ep_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_20ep_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_20ep_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: 1.4422 - Accuracy: 0.6657 ## 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: 3600 - mixed_precision_training: Native AMP ### Training results | Training Loss | Epoch | Step | Validation Loss | Accuracy | |:-------------:|:-------:|:----:|:---------------:|:--------:| | 18.516 | 0.05 | 180 | 4.3268 | 0.0680 | | 14.6282 | 1.0499 | 360 | 3.2382 | 0.3077 | | 9.1983 | 2.0499 | 540 | 2.5109 | 0.4379 | | 5.217 | 3.0501 | 721 | 2.0461 | 0.5148 | | 2.6858 | 4.05 | 901 | 1.7717 | 0.5769 | | 1.2884 | 5.0499 | 1081 | 1.6758 | 0.6006 | | 0.6468 | 6.0499 | 1261 | 1.5235 | 0.6213 | | 0.3398 | 7.0501 | 1442 | 1.4498 | 0.6272 | | 0.1804 | 8.05 | 1622 | 1.4702 | 0.6272 | | 0.1119 | 9.0499 | 1802 | 1.4163 | 0.6302 | | 0.079 | 10.0499 | 1982 | 1.4269 | 0.6538 | | 0.0686 | 11.0501 | 2163 | 1.4097 | 0.6568 | | 0.0626 | 12.05 | 2343 | 1.3878 | 0.6657 | | 0.0485 | 13.0499 | 2523 | 1.4528 | 0.6686 | | 0.0613 | 14.0499 | 2703 | 1.4348 | 0.6627 | | 0.053 | 15.0501 | 2884 | 1.4080 | 0.6716 | | 0.0435 | 16.05 | 3064 | 1.4331 | 0.6627 | | 0.029 | 17.0499 | 3244 | 1.4446 | 0.6568 | | 0.0292 | 18.0499 | 3424 | 1.4439 | 0.6686 | | 0.0199 | 19.0487 | 3600 | 1.4422...

Note24 oct.huggingface.co/Shawon16/timesformer_wlasl_100_20ep_coR_

Source context: 12 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/timesformer_wlasl_100_20ep_coR_

Note6 aoûthuggingface.co/Shawon16/timesformer_wlasl_100_20ep_coR_

Source context: 7 downloads · 0 likes · Pipeline video-classification · Library transformers · Repo Shawon16/timesformer_wlasl_100_20ep_coR_