---
license: apache-2.0
base_model: google-t5/t5-small
tags:
- generated_from_trainer
model-index:
- name: t5-small-samsum
  results: []
datasets:
- samsum
pipeline_tag: summarization
---

<!-- 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-samsum

This model is a fine-tuned version of [google-t5/t5-small](https://huggingface.co/google-t5/t5-small) on an samsum dataset.
It achieves the following results on the evaluation set:
- Loss: 1.6507


## Training procedure

### Training hyperparameters

The following hyperparameters were used during training:
- learning_rate: 2e-05
- train_batch_size: 8
- eval_batch_size: 32
- seed: 42
- gradient_accumulation_steps: 4
- total_train_batch_size: 32
- optimizer: Adam with betas=(0.9,0.999) and epsilon=1e-08
- lr_scheduler_type: linear
- lr_scheduler_warmup_steps: 500
- num_epochs: 64
- mixed_precision_training: Native AMP

### Training results

| Training Loss | Epoch | Step  | Validation Loss |
|:-------------:|:-----:|:-----:|:---------------:|
| No log        | 1.0   | 460   | 1.9598          |
| 2.4944        | 2.0   | 921   | 1.8661          |
| 2.0902        | 3.0   | 1381  | 1.8210          |
| 2.0173        | 4.0   | 1842  | 1.8009          |
| 1.9623        | 5.0   | 2302  | 1.7787          |
| 1.9331        | 6.0   | 2763  | 1.7637          |
| 1.903         | 7.0   | 3223  | 1.7514          |
| 1.881         | 8.0   | 3684  | 1.7390          |
| 1.8648        | 9.0   | 4144  | 1.7350          |
| 1.8463        | 10.0  | 4605  | 1.7242          |
| 1.8302        | 11.0  | 5065  | 1.7189          |
| 1.8119        | 12.0  | 5526  | 1.7098          |
| 1.8119        | 13.0  | 5986  | 1.7076          |
| 1.8007        | 14.0  | 6447  | 1.7057          |
| 1.7903        | 15.0  | 6907  | 1.6984          |
| 1.778         | 16.0  | 7368  | 1.6944          |
| 1.7639        | 17.0  | 7828  | 1.6907          |
| 1.7596        | 18.0  | 8289  | 1.6896          |
| 1.746         | 19.0  | 8749  | 1.6861          |
| 1.7342        | 20.0  | 9210  | 1.6860          |
| 1.732         | 21.0  | 9670  | 1.6808          |
| 1.719         | 22.0  | 10131 | 1.6760          |
| 1.7152        | 23.0  | 10591 | 1.6778          |
| 1.7082        | 24.0  | 11052 | 1.6762          |
| 1.7003        | 25.0  | 11512 | 1.6707          |
| 1.7003        | 26.0  | 11973 | 1.6722          |
| 1.6952        | 27.0  | 12433 | 1.6701          |
| 1.6848        | 28.0  | 12894 | 1.6671          |
| 1.6814        | 29.0  | 13354 | 1.6668          |
| 1.6743        | 30.0  | 13815 | 1.6637          |
| 1.6742        | 31.0  | 14275 | 1.6640          |
| 1.6652        | 32.0  | 14736 | 1.6624          |
| 1.6582        | 33.0  | 15196 | 1.6606          |
| 1.6575        | 34.0  | 15657 | 1.6605          |
| 1.6499        | 35.0  | 16117 | 1.6617          |
| 1.6455        | 36.0  | 16578 | 1.6601          |
| 1.6506        | 37.0  | 17038 | 1.6594          |
| 1.6506        | 38.0  | 17499 | 1.6556          |
| 1.637         | 39.0  | 17959 | 1.6570          |
| 1.6374        | 40.0  | 18420 | 1.6558          |
| 1.6303        | 41.0  | 18880 | 1.6557          |
| 1.6311        | 42.0  | 19341 | 1.6553          |
| 1.6234        | 43.0  | 19801 | 1.6570          |
| 1.619         | 44.0  | 20262 | 1.6537          |
| 1.6214        | 45.0  | 20722 | 1.6529          |
| 1.6183        | 46.0  | 21183 | 1.6542          |
| 1.609         | 47.0  | 21643 | 1.6543          |
| 1.6159        | 48.0  | 22104 | 1.6530          |
| 1.6101        | 49.0  | 22564 | 1.6524          |
| 1.6083        | 50.0  | 23025 | 1.6515          |
| 1.6083        | 51.0  | 23485 | 1.6528          |
| 1.605         | 52.0  | 23946 | 1.6526          |
| 1.6011        | 53.0  | 24406 | 1.6515          |
| 1.6028        | 54.0  | 24867 | 1.6517          |
| 1.6015        | 55.0  | 25327 | 1.6512          |
| 1.601         | 56.0  | 25788 | 1.6504          |
| 1.6007        | 57.0  | 26248 | 1.6513          |
| 1.5948        | 58.0  | 26709 | 1.6511          |
| 1.5973        | 59.0  | 27169 | 1.6515          |
| 1.5929        | 60.0  | 27630 | 1.6514          |
| 1.5955        | 61.0  | 28090 | 1.6507          |
| 1.5931        | 62.0  | 28551 | 1.6507          |
| 1.5939        | 63.0  | 29011 | 1.6507          |
| 1.5939        | 63.93 | 29440 | 1.6507          |


### Framework versions

- Transformers 4.39.1
- Pytorch 2.2.1
- Datasets 2.18.0
- Tokenizers 0.15.2