Instructions to use Sujith2121/flan-t5-agnews-lora with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- PEFT
How to use Sujith2121/flan-t5-agnews-lora with PEFT:
from peft import PeftModel from transformers import AutoModelForSeq2SeqLM base_model = AutoModelForSeq2SeqLM.from_pretrained("google/flan-t5-base") model = PeftModel.from_pretrained(base_model, "Sujith2121/flan-t5-agnews-lora") - Transformers
How to use Sujith2121/flan-t5-agnews-lora with Transformers:
# Load model directly from transformers import AutoModel model = AutoModel.from_pretrained("Sujith2121/flan-t5-agnews-lora", dtype="auto") - Notebooks
- Google Colab
- Kaggle
flan-t5-agnews-lora
This model is a fine-tuned version of google/flan-t5-base on an unknown dataset. It achieves the following results on the evaluation set:
- Loss: 8.7370
- Accuracy: 0.8835
- Precision: 0.9547
- Recall: 0.8835
- F1: 0.9156
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: 0.0005
- train_batch_size: 32
- eval_batch_size: 32
- 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: 3
- mixed_precision_training: Native AMP
Training results
| Training Loss | Epoch | Step | Validation Loss | Accuracy | Precision | Recall | F1 |
|---|---|---|---|---|---|---|---|
| 9.7021 | 1.0 | 625 | 9.0882 | 0.6955 | 0.6118 | 0.6955 | 0.6413 |
| 9.3249 | 2.0 | 1250 | 8.8031 | 0.884 | 0.9537 | 0.884 | 0.9153 |
| 9.2210 | 3.0 | 1875 | 8.7370 | 0.8835 | 0.9547 | 0.8835 | 0.9156 |
Framework versions
- PEFT 0.18.1
- Transformers 5.0.0
- Pytorch 2.10.0+cu128
- Datasets 4.8.3
- Tokenizers 0.22.2
- Downloads last month
- 1
Inference Providers NEW
This model isn't deployed by any Inference Provider. 🙋 Ask for provider support
Model tree for Sujith2121/flan-t5-agnews-lora
Base model
google/flan-t5-base