transformers tensorboard safetensors t5 text2text-generation generated_from_trainer base_model:t5-small license:apache-2.0 autotrain_compatible endpoints_compatible text-generation-inference region:us
---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: HAR_model
  results: []
---

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# HAR_model

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the None dataset.
It achieves the following results on the evaluation set:
- Loss: 2.5524
- Rouge1: 0.3529
- Rouge2: 0.1071
- Rougel: 0.2263
- Rougelsum: 0.2263
- Gen Len: 86.0

## 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: 16
- eval_batch_size: 16
- seed: 42
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- num_epochs: 15
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| No log        | 1.0   | 1    | 2.9579          | 0.312  | 0.0738 | 0.2003 | 0.2003    | 75.0    |
| No log        | 2.0   | 2    | 2.8855          | 0.312  | 0.0738 | 0.2003 | 0.2003    | 75.0    |
| No log        | 3.0   | 3    | 2.8381          | 0.3376 | 0.0808 | 0.205  | 0.205     | 77.5    |
| No log        | 4.0   | 4    | 2.7929          | 0.3383 | 0.0903 | 0.2018 | 0.2018    | 74.5    |
| No log        | 5.0   | 5    | 2.7389          | 0.3383 | 0.0903 | 0.2018 | 0.2018    | 74.5    |
| No log        | 6.0   | 6    | 2.6640          | 0.3383 | 0.0903 | 0.2018 | 0.2018    | 74.5    |
| No log        | 7.0   | 7    | 2.6333          | 0.3422 | 0.0916 | 0.1961 | 0.1961    | 72.0    |
| No log        | 8.0   | 8    | 2.6110          | 0.3383 | 0.0903 | 0.2018 | 0.2018    | 74.5    |
| No log        | 9.0   | 9    | 2.5951          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |
| No log        | 10.0  | 10   | 2.5826          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |
| No log        | 11.0  | 11   | 2.5732          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |
| No log        | 12.0  | 12   | 2.5632          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |
| No log        | 13.0  | 13   | 2.5632          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |
| No log        | 14.0  | 14   | 2.5562          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |
| No log        | 15.0  | 15   | 2.5524          | 0.3529 | 0.1071 | 0.2263 | 0.2263    | 86.0    |


### Framework versions

- Transformers 4.37.2
- Pytorch 2.1.0+cu121
- Datasets 2.17.0
- Tokenizers 0.15.1
