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---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: video_prompt_generation
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. -->
# video_prompt_generation
This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 1.1494
- Rouge1: 0.0
- Rouge2: 0.0
- Rougel: 0.0
- Rougelsum: 0.0
- Gen Len: 0.0
## 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: 2e-05
- train_batch_size: 4
- eval_batch_size: 4
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log | 1.0 | 12 | 9.1895 | 0.035 | 0.0027 | 0.032 | 0.0319 | 5.75 |
| No log | 2.0 | 24 | 5.4070 | 0.0319 | 0.0 | 0.0291 | 0.0292 | 5.75 |
| No log | 3.0 | 36 | 2.9765 | 0.0255 | 0.0 | 0.0228 | 0.0227 | 4.3333 |
| No log | 4.0 | 48 | 1.6960 | 0.0117 | 0.0 | 0.0117 | 0.0117 | 1.5 |
| No log | 5.0 | 60 | 1.3199 | 0.0029 | 0.0 | 0.0029 | 0.0029 | 0.6667 |
| No log | 6.0 | 72 | 1.2154 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 7.0 | 84 | 1.1874 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 8.0 | 96 | 1.1794 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 9.0 | 108 | 1.1652 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
| No log | 10.0 | 120 | 1.1494 | 0.0 | 0.0 | 0.0 | 0.0 | 0.0 |
### Framework versions
- Transformers 4.40.2
- Pytorch 2.2.1+cu121
- Datasets 2.19.1
- Tokenizers 0.19.1
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