---
tags:
- generated_from_trainer
metrics:
- rouge
- bleu
model-index:
- name: timesformer-bert-video-captioning
  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-bert-video-captioning

This model is a fine-tuned version of [](https://huggingface.co/) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 1.2821
- Rouge1: 30.0468
- Rouge2: 8.4998
- Rougel: 29.0632
- Rougelsum: 29.0231
- Bleu: 4.8298
- Gen Len: 9.5332

## 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: 8
- eval_batch_size: 8
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 2

### Training results

| Training Loss | Epoch | Step | Bleu   | Gen Len | Validation Loss | Rouge1  | Rouge2 | Rougel  | Rougelsum |
|:-------------:|:-----:|:----:|:------:|:-------:|:---------------:|:-------:|:------:|:-------:|:---------:|
| 2.4961        | 0.12  | 200  | 1.5879 | 9.5332  | 1.6548          | 25.4717 | 5.11   | 24.6679 | 24.6696   |
| 1.6561        | 0.25  | 400  | 2.3515 | 9.5332  | 1.5339          | 26.1748 | 5.9106 | 25.413  | 25.3958   |
| 1.5772        | 0.37  | 600  | 2.266  | 9.5332  | 1.4510          | 28.6891 | 6.0431 | 27.7387 | 27.8043   |
| 1.492         | 0.49  | 800  | 3.6517 | 9.5332  | 1.3760          | 29.0257 | 7.8515 | 28.3142 | 28.3036   |
| 1.4736        | 0.61  | 1000 | 3.4866 | 9.5332  | 1.3425          | 27.9774 | 6.2175 | 26.7783 | 26.7207   |
| 1.3856        | 0.74  | 1200 | 3.1649 | 9.5332  | 1.3118          | 27.3532 | 6.5569 | 26.4964 | 26.5087   |
| 1.3972        | 0.86  | 1400 | 3.5337 | 9.5332  | 1.2868          | 28.233  | 7.6471 | 27.3651 | 27.3354   |
| 1.374         | 0.98  | 1600 | 3.5737 | 9.5332  | 1.2571          | 28.8216 | 7.542  | 27.9166 | 27.9353   |
| 1.2207        | 1.1   | 1800 | 3.7983 | 9.5332  | 1.3362          | 29.9574 | 8.1088 | 28.8866 | 28.855    |
| 1.1861        | 1.23  | 2000 | 3.6521 | 9.5332  | 1.3295          | 30.072  | 7.7799 | 28.8417 | 28.864    |
| 1.1173        | 1.35  | 2200 | 3.9784 | 9.5332  | 1.3335          | 29.736  | 7.9661 | 28.6877 | 28.6974   |
| 1.1255        | 1.47  | 2400 | 4.3021 | 9.5332  | 1.3097          | 29.8176 | 8.4656 | 28.958  | 28.9571   |
| 1.0909        | 1.6   | 2600 | 1.3095 | 30.0233 | 8.4896          | 29.2562 | 29.2375| 4.4782  | 9.5332    |
| 1.1205        | 1.72  | 2800 | 1.2992 | 29.7164 | 8.007           | 28.5027 | 28.5018| 4.44    | 9.5332    |
| 1.1069        | 1.84  | 3000 | 1.2830 | 29.851  | 8.4312          | 28.8139 | 28.8205| 4.6065  | 9.5332    |
| 1.076         | 1.96  | 3200 | 1.2821 | 30.0468 | 8.4998          | 29.0632 | 29.0231| 4.8298  | 9.5332    |


### Framework versions

- Transformers 4.30.2
- Pytorch 2.0.1+cu118
- Datasets 2.13.1
- Tokenizers 0.13.3