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TimeSformer-GPT2-UCF-UCA-01
Image-Captioning-ML/TimeSformer-GPT2-UCF-UCA-01
TimeSformer-GPT2-UCF-UCA-01 is a image-text-to-text model from Image-Captioning-ML. Use it for the image-text-to-text task on the model card, and read the license before you ship it in a product. It is set up for transformers.
should probably proofread and complete it, then remove this comment. --
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At a glance
- Task
- Image-Text-to-Text
- Library
- transformers
- Model type
- vision-encoder-decoder
- Access
- Public
- Created
- Apr 16, 2025
- Updated
- Apr 17, 2025
- SHA
- 03934d6e
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Base models
Model card
From the Hugging Face model README
<!-- 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-GPT2-UCF-UCA-01
This model is a fine-tuned version of Neleac/SpaceTimeGPT on an unknown dataset. It achieves the following results on the evaluation set:
- eval_loss: 4.3576
- eval_rouge1: 11.969
- eval_rouge2: 0.9894
- eval_rougeL: 11.208
- eval_rougeLsum: 9.6391
- eval_gen_len: 49.0
- eval_runtime: 21.4549
- eval_samples_per_second: 0.466
- eval_steps_per_second: 0.466
- epoch: 0.1412
- step: 1000
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: 1
- eval_batch_size: 1
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 3.0
Framework versions
- Transformers 4.51.1
- Pytorch 2.5.1+cu124
- Datasets 3.5.0
- Tokenizers 0.21.0
- Task
- Image-Text-to-Text
- Library
- transformers
- Type
- vision-encoder-decoder
- Created
- Apr 16, 2025
- Updated
- Apr 17, 2025