---
library_name: transformers
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
datasets:
- samsum
metrics:
- rouge
model-index:
- name: t5-small-transcript-summarizer
  results:
  - task:
      name: Sequence-to-sequence Language Modeling
      type: text2text-generation
    dataset:
      name: samsum
      type: samsum
      config: samsum
      split: validation
      args: samsum
    metrics:
    - name: Rouge1
      type: rouge
      value: 41.4993
---

<!-- 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. -->

# t5-small-transcript-summarizer

This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on the samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.7347
- Rouge1: 41.4993
- Rouge2: 18.6768
- Rougel: 34.8901
- Rougelsum: 38.434
- Gen Len: 16.533

## 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: 4
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss | Rouge1  | Rouge2  | Rougel  | Rougelsum | Gen Len |
|:-------------:|:-----:|:-----:|:---------------:|:-------:|:-------:|:-------:|:---------:|:-------:|
| 1.9691        | 1.0   | 3683  | 1.7864          | 40.9391 | 18.2339 | 34.4773 | 38.0777   | 16.7017 |
| 1.9213        | 2.0   | 7366  | 1.7533          | 41.4658 | 18.8086 | 34.8947 | 38.3528   | 16.5208 |
| 1.8757        | 3.0   | 11049 | 1.7367          | 41.641  | 18.7355 | 35.0432 | 38.5403   | 16.544  |
| 1.8484        | 4.0   | 14732 | 1.7347          | 41.4993 | 18.6768 | 34.8901 | 38.434    | 16.533  |


### Framework versions

- Transformers 4.44.2
- Pytorch 2.4.1+cu121
- Datasets 3.0.1
- Tokenizers 0.19.1