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---
license: apache-2.0
base_model: t5-small
tags:
- generated_from_trainer
metrics:
- rouge
model-index:
- name: summarizer_samsum_model
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. -->
# summarizer_samsum_model
This model is a fine-tuned version of [t5-small](https://huggingface.co/t5-small) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3992
- Rouge1: 0.4144
- Rouge2: 0.1805
- Rougel: 0.3419
- Rougelsum: 0.3418
- Gen Len: 16.6732
## 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: 10
- mixed_precision_training: Native AMP
### Training results
| Training Loss | Epoch | Step | Validation Loss | Rouge1 | Rouge2 | Rougel | Rougelsum | Gen Len |
|:-------------:|:-----:|:----:|:---------------:|:------:|:------:|:------:|:---------:|:-------:|
| 0.4595 | 1.0 | 737 | 0.4170 | 0.3923 | 0.163 | 0.3243 | 0.3242 | 16.1826 |
| 0.4474 | 2.0 | 1474 | 0.4113 | 0.3991 | 0.1685 | 0.3304 | 0.3303 | 16.5925 |
| 0.4416 | 3.0 | 2211 | 0.4092 | 0.4021 | 0.1722 | 0.3337 | 0.3339 | 16.6023 |
| 0.4388 | 4.0 | 2948 | 0.4048 | 0.4062 | 0.1737 | 0.3361 | 0.3361 | 16.5731 |
| 0.4331 | 5.0 | 3685 | 0.4030 | 0.4093 | 0.1758 | 0.3379 | 0.338 | 16.696 |
| 0.4243 | 6.0 | 4422 | 0.4010 | 0.4111 | 0.1778 | 0.3396 | 0.3396 | 16.5728 |
| 0.4234 | 7.0 | 5159 | 0.4000 | 0.4129 | 0.1789 | 0.3406 | 0.3405 | 16.7139 |
| 0.425 | 8.0 | 5896 | 0.3996 | 0.4125 | 0.1797 | 0.3407 | 0.3407 | 16.7089 |
| 0.4247 | 9.0 | 6633 | 0.3993 | 0.4147 | 0.181 | 0.3421 | 0.3422 | 16.6943 |
| 0.4176 | 10.0 | 7370 | 0.3992 | 0.4144 | 0.1805 | 0.3419 | 0.3418 | 16.6732 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.18.0
- Tokenizers 0.15.2
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