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---
license: cc-by-nc-nd-4.0
base_model: google/t5-efficient-base
tags:
- generated_from_trainer
model-index:
- name: checkpoint
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. -->
# how to use the model
```
from transformers import AutoTokenizer, AutoModelForSeq2SeqLM
tokenizer = AutoTokenizer.from_pretrained("piazzola/test2")
model = AutoModelForSeq2SeqLM.from_pretrained("piazzola/test2")
from transformers import pipeline
pipe = pipeline("text2text-generation", model="piazzola/test2")
sentence = "i left the keys in the car."
output = pipe(sentence, max_new_tokens=100, do_sample=True, temperature=0.1)
print(output)
```
# checkpoint
This model is a fine-tuned version of [google/t5-efficient-base](https://huggingface.co/google/t5-efficient-base) on an unknown dataset.
It achieves the following results on the evaluation set:
- Loss: 0.3070
## 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: 3
### Training results
| Training Loss | Epoch | Step | Validation Loss |
|:-------------:|:-----:|:----:|:---------------:|
| No log | 0.3 | 240 | 1.4901 |
| No log | 0.6 | 480 | 0.7750 |
| 3.5263 | 0.9 | 720 | 0.5219 |
| 3.5263 | 1.2 | 960 | 0.3782 |
| 0.607 | 1.5 | 1200 | 0.3521 |
| 0.607 | 1.8 | 1440 | 0.3356 |
| 0.4173 | 2.1 | 1680 | 0.3255 |
| 0.4173 | 2.4 | 1920 | 0.3151 |
| 0.368 | 2.7 | 2160 | 0.3093 |
| 0.368 | 3.0 | 2400 | 0.3070 |
### Framework versions
- Transformers 4.38.2
- Pytorch 2.2.1+cu121
- Datasets 2.17.1
- Tokenizers 0.15.2 |