Instructions to use ivanenclonar/typhoon-t5-finetuned with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use ivanenclonar/typhoon-t5-finetuned with Transformers:
# Load model directly from transformers import AutoTokenizer, AutoModelForSeq2SeqLM tokenizer = AutoTokenizer.from_pretrained("ivanenclonar/typhoon-t5-finetuned") model = AutoModelForSeq2SeqLM.from_pretrained("ivanenclonar/typhoon-t5-finetuned") - Notebooks
- Google Colab
- Kaggle
typhoon-t5-finetuned
This model is a fine-tuned version of ivanenclonar/typhoon-t5-pretrained on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 0.3899
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: 64
- eval_batch_size: 64
- seed: 42
- optimizer: Use OptimizerNames.ADAMW_TORCH_FUSED with betas=(0.9,0.999) and epsilon=1e-08 and optimizer_args=No additional optimizer arguments
- lr_scheduler_type: linear
- num_epochs: 15
Training results
| Training Loss | Epoch | Step | Validation Loss |
|---|---|---|---|
| No log | 1.0 | 35 | 0.7777 |
| No log | 2.0 | 70 | 0.5711 |
| No log | 3.0 | 105 | 0.5039 |
| No log | 4.0 | 140 | 0.4666 |
| No log | 5.0 | 175 | 0.4435 |
| No log | 6.0 | 210 | 0.4294 |
| No log | 7.0 | 245 | 0.4184 |
| No log | 8.0 | 280 | 0.4104 |
| No log | 9.0 | 315 | 0.4042 |
| No log | 10.0 | 350 | 0.3996 |
| No log | 11.0 | 385 | 0.3959 |
| No log | 12.0 | 420 | 0.3932 |
| No log | 13.0 | 455 | 0.3913 |
| No log | 14.0 | 490 | 0.3903 |
| 0.6133 | 15.0 | 525 | 0.3899 |
Framework versions
- Transformers 4.56.0
- Pytorch 2.8.0+cu129
- Datasets 4.4.2
- Tokenizers 0.22.0
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support